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Original research article, the fourth industrial revolution – smart technology, artificial intelligence, robotics and algorithms: industrial psychologists in future workplaces.

• Department of Industrial and Organisational Psychology, University of South Africa, Pretoria, South Africa

In the Fourth Industrial Revolution (4IR), STARA (smart technology, artificial intelligence, robotics, and algorithms) is predicted to replace a third of the jobs that exist today. Almost twice as many current work tasks will be handled by robots. It is forecast that by 2025, 85 million jobs may be displaced by a shift in the division of labor between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines and algorithms. Industrial psychologists are playing an increasingly important role in the workplace due to these trends from a strategic intelligence perspective. The objective of this article is to present a critical review of industrial psychologists in future workplaces in the context of the 4IR - STARA. A competence model is posed for industrial psychologists to perform a strategic intelligence role in organizations in the 4IR.

Introduction

Industrial psychologists have a key role to play in strategic and operational human resources (personnel) practice and people (individual, group, and organizations) behavior dynamics, as well as assessment and intervention design. The industrial psychologist's strategic intelligence role is indispensible in realizing an organization's success. The value of strategic intelligence can be enhanced by improving the skills of managers and employees, which in turn improves their ability to learn about the potential 4IR changes in their organization, by allowing them to communicate freely to share their perceptions, new information, and insights whenever and wherever the organization requires such information, the “intelligence quotient” of all organizational managers and employees will be increased ( Ogbeibu et al., 2021c ).

Accordingly, industrial psychologists apply psychology in the workplace, provide interventions to modify poor performance and implement programmes for industrial psychology intervention ( Graupner, 2021 ). In the human workforce, there is a mandate for advancement ( Jackson, 2014 ). Advances in technology, and the associated benefits and drawbacks, are critical issues regarding the workforce that merit in-depth discussions. Although the workforce may undergo a transformation over a century, Elliott (2014) suggests that organizations need to understand the capabilities of technology and how it will affect employee behavior in the next 10 years or so ( Chuang and Graham, 2018 ). The growth of smart technology, artificial intelligence (AI), robotics, and algorithms, or STARA ( Bort, 2014 ; Lynch, 2015 ), has led Stephen Hawking and Bill Gates to warn that mass unemployment will result ( Bort, 2014 ; Lynch, 2015 ).

STARA is estimated to eliminate 33% of occupations by 2025 ( Frey and Osborne, 2013 ; Thibodeau, 2014 ) due to improvements in robotic dexterity and intelligence, combined with the development of low-cost autonomous units that can potentially outperform people in a wide variety of work settings and dynamic activities ( World Economic Forum, 2020 ). The web of things, self-checkout systems in retail, cellphone applications, bookkeeping robotisation, and driverless vehicles are examples of these types of innovations. As a result of these types of innovation, it is impossible to imagine prolonging workers in certain positions due to cost advantages. In addition, recent debates emphasize the importance of teams to collaborate digitally and interdependently on set tasks, and for industrial psychologists to develop competencies fundamental to the STARA model, to catalyze innovation initiatives and reduce turnover expectations ( Brougham and Haar, 2018 ; Ding, 2021 ; Ogbeibu et al., 2021a ).

STARA is not simply being tapped into low-paying, low-talented jobs. There is greater use of high-tech algorithms in research, and information-writing algorithms are becoming more advanced in organizations and communications in general. Robots with high-precision finesse are being used increasingly as well. In an investigation of 702 professions, the likelihood of STARA claiming employment was identified. Accounting, commercial pilots, client management, sales, and office workers are among the occupations at risk ( Frey and Osborne, 2013 ; Bhargava et al., 2021 ). In addition, STARA could have a substantial impact on healthcare ( Bloss, 2011 ; Lorentziadis, 2014 ), education (for example, through web-based learning), transportation, and farming. In general, STARA threatens to eliminate 47% of occupations ( Brougham and Haar, 2018 ).

South Africa's President Cyril Ramaphosa has incorporated the Fourth Industrial Revolution (4IR) into his economic strategy, provoking criticism for its neoliberal rhetoric echoing the World Economic Forum (WEF) and concern that it will not lead to job creation. Corporations must rethink their strategies and auto-cannibalize their business models. Historically, it has been considered a way for policymakers in manufacturing nations to increase national competitiveness and bring manufacturing in-house. However, it may prevent developing countries from attracting labor-intensive manufacturing that would create jobs ( Hu, 2021 ). This could reduce the demand for low-skilled workers and increase inequality by reducing the demand for work. Due to deficiencies in the education system, South Africa has a significant skills shortage, limiting the supply of managers, researchers, and workers for 4IR ( Venturini, 2022 ). The poor quality of infrastructure reflects poor governance and state capture. In the cybersecurity and data protection arenas, it has a poor track record in policy formulation and implementation. Despite aspirations, the domestic market is small, and access to the rest of Africa is difficult due to its limited purchasing power and poor distribution system. Moreover, South African firms must compete with strong Chinese firms ( Sutherland, 2020 ).

Objective of This Article

The objective of this article is to present a critical review of industrial psychologists in future workplaces in the context of the 4IR - STARA. A competence model is posed for industrial psychologists to perform a strategic intelligence role in organizations in the 4IR.

The subsequent section, the literature review focus on the emergence of digital workspaces in the fourth industrial revolution, and conceptualization of smart technology, artificial intelligence, robotics and algorithms (STARA).

Literature Review

The emergence of digital workspaces in the fourth industrial revolution.

In 4IR, people, objects and systems are interconnected through the real-time exchange of data throughout the entire value chain, resulting in an increasingly digitized world. A significant characteristic of this society is the proliferation of increasingly complex technologies, which integrate the physical, digital, and biological worlds ( Spath et al., 2013 ; Dorst et al., 2015 ; Rotatori et al., 2021 ). This interconnection leads to the advent of products, machines, and processes equipped with artificial intelligence and capable of adapting to spontaneous changes in their environment. In addition, smart technology becomes integrated into broader systems, enhancing the ability to create flexible, self-operating production systems. Smart technology and systems can be applied to a broad range of fields ( Huber and Kaiser, 2015 ; Porter and Heppelmann, 2015 ; Hecklau et al., 2016 ).

The 4IR's core component involves autonomous production methods powered by robots, which carry out tasks intelligently while focusing on safety, flexibility, versatility, and coordination. Automation will result in job losses, which means industrial psychologists will have to assist people with coping with the loss of their jobs. The 4IR may indeed enhance access to mental-health services, even if automation can adversely affect some aspects of people's wellbeing. Two examples of the use of AI to provide mental health services are the use of Woebot, the world's first mental-health chatbot, and Tess, built by psychologists to coach people to build resilience by having text message conversations—similar to talking to a friend or coach ( Gower, 2018 ). Integrating robots into human workspaces, however, helps it to become more economic and productive, and opens many possibilities in industries ( Cheng et al., 2021 ). With the latest technological innovation, industrial robots are evolving to facilitate the 4IR ( Roland Berger Strategy Consultants, 2014 ). As they work together in the 4IR, humans and robots will interlink tasks and use smart sensors to create human-machine interfaces. Various functions can now be performed by robots, including production, logistics, and office management (to distribute documents), and they can be controlled remotely.

This implies that the 4IR is based on cyber-physical systems, the Internet of Things, and the Internet of Services. There is a growing number of companies joining the movement and using various approaches to enhance competitiveness and gain productivity and economic benefits from it ( Trauth-Goik, 2021 ). Although the 4IR covers a wide array of manufacturing applications, the trend is quickly taking shape through the emergence of robotics and automation product innovations that are specifically designed for the industrial revolution. According to Hecklau et al. (2016) , the 4IR presents many opportunities for companies; however, there are also many challenges as a result of ongoing digitisation and automation.

Financial Challenges

As globalization continues, organizations must deal with shorter product life cycles, the need to remain competitive, and reduced time to market ( Helmrich, 2015 ). To achieve an advanced level of service orientation, organizations must rationalize their innovation processes ( Shahd and Hampe, 2015 ; Hecklau et al., 2016 ; Umar et al., 2021 ). Finance and process-driven roles are on the decline while roles that require thinking outside the box are gaining traction and will be in demand. However, customers must still be persuaded that technology will improve their lives. The cloud and big data are particular developments that are affecting all businesses. Customers are becoming more empowered through technology and data. The power of technology cannot be underestimated. As a result, the future pricing models and unit costs of finance will change. Cloud technology is also safe and allows updates to be completed seamlessly. Data can be accessed anywhere and anytime, which has fundamentally changed how businesses operate. Real-time reporting has also fundamentally changed how businesses operate. Business leaders can receive more information directly in the format they prefer ( Nyambo, 2020 ).

Societal Challenges

Young employees need to be attracted while older employees need to be retained for their expertise. Social values among younger generations are work-life balance and balancing work with family ( Stock-Homburg, 2013 ). A growing number of virtual jobs and flexible work topics also call for new forms of lifelong learning ( Brühl, 2015 ). The multifaceted nature of processes is creating jobs requiring more qualifications. To qualify employees for more strategic, coordinating, and creative responsibilities, organizations must provide them with more training in these areas ( Hecklau et al., 2016 ; Rotatori et al., 2021 ).

Technical Challenges

Big data present many challenges to companies ( Huber and Kaiser, 2015 ). Communication networks and internet protocols are among the many information technology infrastructures that need to be built and implemented ( Brühl, 2015 ). To facilitate cooperative work on different platforms, standardized interfaces and open architectures should be created ( Shahd and Hampe, 2015 ). Keeping large amounts of data on external servers raises the issue of cybersecurity since unauthorized access to the data must be prevented. Further training is needed for employees to adapt to the increased use of virtual work ( Hecklau et al., 2016 ; Ross and Maynard, 2021 ).

Ecological Challenges

Climate change is one of the most significant challenges facing the environment ( Elheddad et al., 2021 ). All living creatures within the biosphere are affected by the continuous changes occurring within the environment. It is also increasingly important to use ecological resources efficiently since many of them are scarce. Consequently, organizations are increasingly recognizing their role in implementing sustainable solutions ( Spath et al., 2013 ; Hecklau et al., 2016 ).

Political and Legal Challenges

Governments must support organizations in developing new technologies, as well as incorporating those technologies into the current environment. Governments should also establish legal parameters for the use of big data. While interacting with smart objects, data will be collected on each system as a result of the interaction ( Brühl, 2015 ). Considering increasing work flexibility, policies and procedures regarding work times and safety matters must be established to protect employees ( Hecklau et al., 2016 ). Governments could find themselves increasingly powerless against megacorporations, the Exponential Organizations. Regulating the activities of these global behemoths (and raising taxes from them) may be beyond the grasp of governments. If government agencies are too slow to adopt new technologies, they will both fail to generate the efficiency gains needed to keep public services going, and damage the reputation of government ( Lye, 2017 ).

Smart Technology, Artificial Intelligence, Robotics and Algorithms

Industrial psychologists are faced with one of the biggest issues of their times: What impact will the march of STARA have on either where people work or how people work in the future? Do we need to work in the future? Where do they fit in a world of automation? Automation is predicted to impact careers and the workplace in many ways, many analysts focus on smart technology. Luz Tortorella et al. (2021) point out that the real story has less to do with technology and more to do with how humans choose to use it. A complex, changing and competitive set of forces will determine the shape that the workforce of the future takes. Although some of these forces are evident, we cannot predict the pace at which they will manifest. As the transition to an automated workplace progresses, policies and laws, governments that enforce them, and consumer, employee, and citizen sentiments will all influence its fate. Careers in 2030 will be shaped by how this battle plays out ( Kojm, 2012 ). It is impossible to predict linearly what will happen when so many factors are at play. Organizations, governments, industrial psychologists, and individuals must be prepared for a wide range of outcomes, even those that may appear unlikely ( Stubbings, 2018 ).

Smart Technology

During the last few decades, wireless communication and sensing smart technologies have made it possible for smart learning environments to detect the context of the environment and quantify the attention available to an employee. Durães et al. (2018 ) point out that the development of smart learning environments is based on the rapid progress of wireless communication and sensing smart technologies. Computer scientists refer to a smart environment as a digitally augmented physical environment where sensor-enabled and networked devices work continuously and collaboratively to improve the standard of living for citizens ( Chang and Chen, 2021 ). Today, smart environments are becoming a reality thanks to developments in technology such as mobile communications, wireless sensors, pervasive computing, machine learning, robotics, middleware and agent technology, and human-computer interfaces. As defined by Cook and Das (2005) , the concept “smart” refers to the ability to autonomously acquire and apply knowledge, while the concept “environment” refers to an employee's surroundings.

In conjunction with this technological advancement, job opportunities have evolved, bringing about numerous and wide-ranging changes. There is a growing concern about indicators that are tarnished by changes, such as the need to react quickly to changes, which, in severe cases, can compromise the life and wellbeing of employees. When moderated, it impedes general cognitive abilities, concentration and productivity. Many of these careers are so-called desk jobs, in which people often work more than 8 h every day ( Liao and Drury, 2000 ; Durães et al., 2018 ).

Artificial Intelligence

Digital platforms and artificial intelligence can shape and underpin the world of work in an unlimited way ( Haefner et al., 2021 ). In this platform stratum, the value chain is digitalized, and the back office is commoditised automated. This also comes with warnings. As a trading platform can flourish, it can also take over the entire financial system, putting it at risk to cyberattacks and manipulation on a broad scale ( United Nations Department of Economic Social Affairs, 2010 ). Digital platforms are closely linked to data. Every world—even the most human-centric—is shaped by how governments, organizations and individuals share and use data. Artificial intelligence in the form of digital assistants and machine learning (ML), a branch of AI that mimics the way humans learn, is increasing in accuracy as they use data and algorithms to imitate this process. The system could understand, learn, and act based on the information it gathered.

There are three levels of artificial intelligence. With assisted intelligence, people and organizations can enhance what they are already doing. GPS navigation software, for example, offers drivers directions and adjusts to road conditions. In the era of augmented intelligence, individuals and organizations can do things that would otherwise be impossible ( Haefner et al., 2021 ). Shuttle services, for instance, would not exist without a combination of programmes that manage them. Intelligent machines that act independently will be developed in the future through autonomous intelligence. When they become more widely used, self-driving vehicles could be an example. Using AI to help humanity process, analyze and evaluate the massive amounts of data that create today's world, could allow mankind to spend more time engaged in creative thinking, decision-making and problem-solving ( Stubbings, 2017 , 2018 ).

The advancement of big data and technology is heavily reliant on artificial intelligence and machine learning. It is inherently multidisciplinary, which makes it difficult to understand, evaluate and exploit these technologies. It is true that most companies developing AI or machine learning with a nexus to human resources will have teams composed of engineers, computer scientists, developers, data scientists and other math- and tech-savvy people ( Raisch and Krakowski, 2021 ). In the field of industrial psychology, AI/ML applications are on the rise. Thus, technology remains the focus, a trend likely to continue for some time. A field such as industrial psychology is more susceptible to getting lost in the shuffle during a technology-dominated environment and losing sight of the critical role that industrial psychologists can play ( Putka and Dorsey, 2018 ).

Until recently, most robots were slaves to their human operators; now they are becoming increasingly autonomous and powerful. As robots are increasingly used, the question arises of how robots can be successfully integrated into human-robot teams. According to Richards (2017a) , humans and machines, or “agent” members, can share goals through delegation. The increased power and capacity of robots have caused a great deal of paranoia ( Righetti and Smart, 2021 ). Reports in the media suggest that robots may soon usurp large segments of today's workforce, particularly in industries that already use advanced automation. This is probably a reasonable concern. The number of robots sold worldwide in 2014 increased by 29% to 229,261 units. Robots give humans the ability to withdraw from monotonous, risky, or challenging tasks ( Richards, 2017a ).

The advancement of robotics will pose more questions about robot-human integration as advanced robotics takes expansion to an entirely new level. Modern robot designs can become agent-based models (ABMs) that can be connected to other robots as well as to a wider network made up of humans and machines. This trend is already gaining momentum. Robots and humans work together daily in advanced space systems. Museum visitors may be accompanied by robot tour guides, and some hospitals have already used robot assistants. People, especially those who are frail or aged, will be able to receive help through ABMs soon. In advanced industrial plants, robots will increasingly work as part of a human-agent team ( Tresa et al., 2021 ).

For a group to function well, trust must be of a specific nature. Up until now, most robots have been working as slaves under human supervision. Sources of information provided by them have been unsurprising, making it easy to understand their intentions. Those robots can easily be integrated. Yet, as the operators gain more autonomy, a human-robot relationship will need an increased level of adaptability when considering the assignment of power. People and robots could communicate more effectively if there were a formal system of control in place ( Bhargava et al., 2021 ). Two distinct ways exist for human operators to see the robot components. As an alternative, a bottom-up methodology would mean that ABMs would continue to serve as simple machines that satisfy human objectives. Alternatively, the ABMs could be considered equivalent to individuals within the group using a top-down methodology. According to Richards (2017b) , a top-down methodology would allow the elements to shape similarly to customary human groups, with characterized jobs and norms of conduct.

Eventually, as robots become more autonomous, monitoring may become necessary. Monitoring could be the responsibility of human supervisors. Although security systems may be automated to perform repetitive tasks, a human is still required to monitor their performance to ensure quality. However, a human must authorize an ABM to perform the last activity. The robot could be allowed to perform more important tasks if security were not a concern. Richards (2017b) further indicates that the individual becomes a manager of a human group during the developed phase of ABM self-rule. The implications of this are numerous. A human manager may, in general, prove to be more appealing to many workers. Additionally, Richards (2017b) states that people would usually scrutinize a manager's idea of what tasks to perform if a robot became one. It is just that other robots within the group would not suggest such discussions without specifically intending to do so ( Alcover et al., 2021 ).

For industrial psychologists to analyze robot-human groups only from a quantitative perspective is insufficient. Human relationships will be affected by robots in groups over a prolonged period if robots are present in a group. How will this affect trust within the organization? It may be that profitability increases initially but relationships within the group change as errors are perceived as becoming routine. The findings of investigations that emerge through human-robot collaboration may eventually become less fundamental. The rise of AI could lead to robots being viewed as social specialists. There is a risk that a group can become self-contained with “limited wisdom” ( Richards, 2017b ).

Economic and policy makers hoped that the rise of the internet would lower labor market search costs and improve market outcomes. A design platform provides information on products and trades but in many cases, it also generates recommendations about whom to trade with or what to buy ( Resnick and Varian, 1997 ; Adomavicius and Tuzhilin, 2005 ; Varian, 2010 ; Horton, 2017 ). In an algorithmic system, preferences can be inferred, the possible choices identified and then forced optimisation problems solved for the would-be buyer. Algorithmic systems can incorporate information that no single party is aware of. Furthermore, the quality of these recommendations increases with scale, and they have zero marginal cost.

At the moment, algorithmic recommendations are rare in the labor market; however, as more labor market aspects become computer-mediated, recommendations will become more valid. Nevertheless, labor market recommendations do not seem to be able to significantly improve what employers themselves can accomplish. By assessing qualities that are difficult to capture in a statistical model, industrial psychologists assist in choosing the right candidate for a particular job opening. Employers might not find it that expensive to assemble a pool of reasonable applicants. An issue with recommendations is that, from the employer's perspective, they encourage employers to give preference to some employees and ignore others. In conventional labor markets, some job search assistance programmes have shown strong crowd-out effects ( Crépon et al., 2013 ). From a social welfare perspective, recommendation interventions are less attractive ( Moser et al., 2021 ).

It was concluded by Horton (2017) that algorithmic recommendations can both be acted upon by employers and be effective at increasing the hiring of high-quality candidates, at least for certain kinds of job openings. Even though the algorithm functions as a “black box,” it produces recommendations strikingly similar to those that employers recruit if they do not receive these recommendations, at least within the limits of available measurements and statistical power. As such, algorithmic recommendations are a useful substitute for costly employer efforts. The relationship between job openings and workers seems superficially symmetric; job openings can easily be created and destroyed by employers at will, and workers can enter and leave the labor market, but it seems more likely that employers' decisions to create and fill a job opening are elastomeric in terms of assistance than an individual worker's participation in the labor force. Comparing the conventional market analogy with the alternative, for-profit recruiting firms offer their services mostly to businesses rather than individuals. A platform-based intervention becomes more powerful and possible as more of the labor market is mediated by computers. Platforms collect a great deal of data on market behavior and outcomes, and they have virtually complete control over the details that market participants can see and when. Those changes would have profound consequences for labor markets in terms of equity and efficiency ( Tsamados et al., 2021 ).

The Role of Industrial Psychologists From a Strategic Intelligence Perspective

Waghmare (2019) asserts that strategic intelligence is a highly effective source of competitive advantage since it can enhance decision making because it is based on information. It is important for industrial psychologists to focus on both people and technology in order to make the strategic intelligence process successful. Strategic intelligence is reflected in the industrial psychologist's ability to maintain reputation even when facing challenges that require critical decisions. Esmaeili (2014) proposes that strategic intelligence positively and meaningfully influences strategic decision-making and strategic planning in organizations that use intelligent systems. Additionally, the most effective factors for strategic intelligence include human resource intelligence, organizational process, technology (STARA), informational resources, financial resources, competitor intelligence, and customer intelligence ( Ogbeibu et al., 2021b ). Abdullah (2012) suggests that industrial psychologists need to focus on strategic leadership as a means of developing strategic intelligence. Industrial psychologists use strategic leadership to influence favorable prospects for success; but it also impacts organizational culture, resources allocation, political guidance, and consensus in the uncertain and complex global 4IR environment. Acros (2015) notes that strategic intelligence is crucial to deal with the rapid changes created by the 4IR environment, as well as adapting plans to a dynamic and changing environment.

In almost every application of intelligence, strategic intelligence serves two distinct purposes: one is for management, and the other is focused on operational and functional aspects. In strategic intelligence, questions pertaining to mission, goals, objectives, programs, and resource planning are dealt with as they pertain to management and executive functions ( Waghmare, 2019 ). By contrast, operational intelligence is intelligence that services the needs of supervisors and line managers and focuses on the immediate, routine, and on-going activities of the frontline functions of an organization. An operation intelligence action involves identifying, targeting, detecting, and intervening (or prohibiting) illegal operations in any form. Organizational cultures need to embrace strategic intelligence.

For industrial psychologists, strategic intelligence is about having the right information at the right time to make the right decisions for the future success of their organization. The value of strategic intelligence can be seen in industrial psychologists' ability to maintain reputation even when faced with challenges that require critical decisions. Industrial psychologists are capable of identifying potential threats and changes that have taken place, and with the assistance of intelligence information at hand, can make suggestions to solve the mystery ( Tham and Kim, 2002 ). In strategic intelligence, past and present issues are less important than the future as it looks to predict and anticipate the 4IR future and model it in a way that aligns with operations of the organization. In order for an organization to survive in a competitive market, it needs to understand its key points of improvement and the opportunities available to do so ( Waghmare, 2019 ).

To develop insights and intelligence about future trends in 4IR, industrial psychologists can choose between functional and process approaches to strategic intelligence. An organization's strategic intelligence is often limited to isolated data sets created by individual departments, which apply their knowledge of the company's direction and strategies for success. As a result, information is rarely shared with other levels of managers within an organization, resulting in inferior decisions being made ( Waghmare, 2019 ). Industrial psychologists can assist functionally oriented organizations to overcome barriers to sharing and utilizing strategic intelligence to shape a 4IR future. Strategic intelligence is best organized using a process-based approach. However, in some cases, such as mergers, the industrial psychologist might be required to keep the information confidential and only share it with a few executives.

An organization that develops processes to allow information sharing across business units and geographies will generally benefit from a more disseminated approach. In both approaches there are risks, but the benefits gained by the process approach are significantly greater than those gained by the functional approach. It is not an easy task to develop mature information capabilities to build a strong process approach ( Waghmare, 2019 ). During a process approach, industrial psychologists must remain determined and focused on improving information capabilities. Due to rapid technological, structural, and disruptive changes, the strategic intelligence role of Industrial Psychologists in South Africa is of critical importance for organizations to guide them in the 4IR process. Also, Industrial Psychologists plays a pivotal role toward the understanding of the subjective “lived-through” feelings and experiences of employees and in situ responses to 4IR events.

The methodology applied in this study is depicted in the succeeding section in terms of the study design, eligibility criteria, data analysis, and the strategies used to ensure data quality.

Study Design

The critical review of the research literature entailed a broad systematic review of contemporary research on the themes of the 4IR-STARA. This approach allowed the author to evaluate documented research on the strategic intelligence role of industrial psychologists in future workplaces.

Study Eligibility Criteria

The systematic review was limited to research published between 2015 and 2022 on documented contemporary topics in industrial psychology. EBSCOhost/Academic Search Premier and Google Scholar, an online information technology service, were used to conduct the search. The search terms used were 4IR Smart technology, Artificial intelligence, Robotics, Algorithms (STARA), strategic intelligence and industrial psychology. To identify which articles should be included or excluded from the systematic review, the full texts of publications were downloaded from the databases. Studies exploring industrial psychologists in future workplaces met the inclusion criteria for this article. The research articles were used as data sources.

Data Analysis

A qualitative exploratory approach was used to explore the 4IR-STARA, and the strategic intelligence role of industrial psychologists in the future workplace ( Cresswell, 2014 ). First, the author carefully read the studies to gain a better understanding of the phenomenon under investigation, 4IR-STARA and strategic intelligence role of industrial psychologists. In the second stage, the author synthesized a portrait of 4IR-STARA and the strategic intelligence role of industrial psychologists that considered its relations and connections within its aspects. The third stage consisted of theorizing about how and why these 4IR-STARA and the strategic intelligence role of industrial psychologists relationships exist as they do, and the fourth stage consisted of re-contextualizing the new knowledge about 4IR-STARA and the strategic intelligence role of industrial psychologists phenomena and relationships back into the context of how other authors have articulated the evolving knowledge. EBSCOhost/Academic Search Premier and Google Scholar academic databases were searched for relevant research published between January 2015 and January 2022 to locate 48 studies. Based on a quality assessment of publications, eight studies were identified as the primary sources of information.

Strategies Used to Ensure Data Quality

Analytical processes that are systematic, rigorous, and auditable are among the most significant factors separating high-quality research from poor quality. As a result, the researcher articulated the findings in a way that the outcomes developed by the researcher are accessible to a critical reader, the association between actual data and the conclusions about the actual data is made explicit, and the claims related to the data set are rendered credible. In addition to the potential publication bias, consideration was also given to trustworthiness or credibility, true value and quality, appropriateness, and reflection on the research endeavor, as well as sound practice. By reviewing each article for scientific and methodological rigor and comparing them to the 4IR-STARA, and in terms of the strategic intelligence role of industrial psychologists in the future workplace, the articles' value and quality were assured. All data was retained for future review.

The findings of the study are presented in the following section in terms of Industrial psychology and the maturation of artificial intelligence and machine learning technology. A STARA competence model for industrial psychologists in the 4IR is proposed.

Industrial Psychology and the Maturation of Artificial Intelligence and Machine Learning Technology

Organizations manage an increasing amount of information and technology related to human resources. Increasing amounts of information are accumulating, they are becoming more sophisticated, and they are coming in a variety of forms (for example, big data). Although technological advances are emerging that can assimilate such information, they sprout faster than institutions can absorb, and faster than science can systematically assess. Organizational leaders have been racing to determine how to harness this brand-new wealth of information and technology, but in a rapidly advancing environment, it is easy to feel overwhelmed. Managers must consider difficult downstream questions when considering the value of industrial psychology beyond the publicity surrounding AI/ML human resource technology. When it comes to assessing AI/ML technology for human resource management, industrial psychology benefits leaders not only in sifting through the wheat from the chaff but also in designing a robust AI/ML human resource management system for their organization in the first place. This article poses and answers five questions about the role of industrial psychology in AI/ML assessment and creation ( Putka and Dorsey, 2018 ).

When AI/ML technology is used to make predictions or forecasts, how does it ensure data integrity? To ensure data integrity, a person or a team must be responsible, not a machine. With regard to objectively assessing the value of 'people data' and using that data to make extrapolations, industrial psychology offers a depth and experience that exceeds many other fields. How can AI/ML technology developers verify the effectiveness of what it produces? In the context of decades-old professional principles and standards, “evidence” needs to stand up to judgement. Research and practice in the field of industrial psychology and related scientific fields provide insights into how people's psychological characteristics, behavior, and emotions can be assessed, predicted, and explained.

A developer of an application could verifyn that it will be demonstrably beneficial to an organization. Through the implementation of this technology, organizations will save 20 per cent on turnover among new employees. There is a wide variance in the quality of the proof used to support various assertions about what AI/ML can accomplish. An industrial psychologist is qualified to assess the quality of the findings and data gathered to evaluate AI/ML-related human resource technologies. What are the chances that the technology application will have unfavorable effects? It may be that an AI/ML human-resource application is worth its price if it delivers on its promises (for instance, if it reduces turnover, increases hiring speed, and increases employee engagement or competence). Organizations are reluctant to acknowledge problems, such as a reduction in employee diversity, a violation of employment laws, or a breach of employee confidentiality. An industrial psychologist has extensive experience with the trade-offs and results that result from various assessment and decision-making approaches in the employment sphere. Without understanding why the technology “works” and having subject knowledge of the content involved, it can be very hard to predict as many of these unplanned consequences.

What makes the technology work? Employment decisions do not happen in a vacuum. A multitude of regulatory environments becomes even more complex when working across jurisdictions (for example, employment and data privacy laws). Since legal requirements have generated workforce decisions, the discipline of industrial psychology has been incorporated into these matters. Industrial psychology has a fundamental role to play here. To assess its defensibility from a governing perspective, it is important to understand why the technology produces the results it does. The use of AI/ML technology has more implications than just legal implications for organizations. In technology implementation, intrinsic trust is often overlooked as a key factor. Alternatively, consider a manager in charge of promoting employees who receive assistance from a machine regarding guidance or career opportunities. The “why” behind recommendations made to managers and employees must be communicated. Research in the area of “explainable AI” is quite active but such studies can only gain from the knowledge of the theory and usage of subject-matter knowledge. Industrial psychologists are well-prepared to assist in explaining what is transpiring “below the surface” of a situation because they are educated in assessment and original theories.

Does industrial psychology lead the way in AI/ML technology change, or is it simply standing on the outside looking in, hoping to change the discussion at a later date? Putka and Dorsey (2018) note that industrial psychologists play a more prominent role when conducting AI/ML-based research and constructing sophisticated applications of the technology. Industrial psychology plays an essential role in shaping the great guarantee of AI/ML technology implementation, as well as contributing to the greater mission of the field, which is to nurture and enhance human flourishing as well as long-term business performance and sustainability.

STARA Competence Model for Industrial Psychologists in the Fourth Industrial Revolution

STARA creates many new opportunities for organizations but at the same time, several challenges are arising from the ongoing automation and digitisation. A STARA competence model for industrial psychologists in the 4IR is proposed. The competencies are clustered into four main categories of competencies.

Specialized Competencies

• STARA knowledge : Considering industrial psychologists' cumulative task accountability, STARA knowledge is gaining importance.

• Strategic business : Changing from operational to more strategic functions require specialized all-encompassing competencies. The role of industrial psychologists is to increase the effectiveness of the business. Industrial psychologists must be able to add value through competitive market insights, personal capital, business influence, having the skills to get the job done, and promote agility across the entire organization ( Ulrich, 2021 ).

• Advances human capability : Industrial psychologists must advance human capacity in an organization. In this role, line managers are responsible for elevating and developing talent, and for implementing human resources solutions that enhance both individual talent (human) and organizational capability (capability). Moreover, it provides a specific focus on promoting diversity, equity, and inclusion in the workplace to improve overall organizational performance ( Ulrich, 2021 ).

• Process comprehension : Industrial psychologists need to have a deeper and broader understanding of process intricacy because of advanced process complexity.

• Media abilities : Technological and media skills are required for accumulative virtual work by industrial psychologists.

• Programming abilities : Digitalization and algorithms have led to a high demand for industrial psychologists who have programming skills.

• Understanding information technology security : Industrial psychologists need to understand cybersecurity because of virtual functions on servers and platforms ( Hecklau et al., 2016 ).

Methodological Competencies

• Simplifies complexity : The 4IR presents many challenges for industrial psychologists, and they need to be objective when considering them. During times of uncertainty or crisis, it demonstrates an ability to distinguish signals from noise, think independently and see opportunities ( Ulrich, 2021 ).

• Mobilizes information : By using 4IR technology, industrial psychologists can access, analyze, and act on data to solve problems and make informed decisions. It reflects comfort with data-driven decision-making, a keen interest in technological advancements, and a knowledgeable understanding of social issues that will impact the organization. The industrial psychologist must be able to constantly learn and adapt to the fluctuating artificial intelligence environments ( Ulrich, 2021 ).

• Creativity : The need for more smart technology and innovative products, as well as for internal enhancements, calls for the creativity of industrial psychologists.

• Innovative thinking : Industrial psychologists could play a more active role in strategic functions, thus being innovators.

• Problem solving : Industrial psychologists should improve processes and procedures.

• Conflict solving : An advanced service emphasis increases customer associations; thus, industrial psychologists need to resolve conflicts.

• Decision-making : Industrial psychologists will be required to make their own decisions since they will be held more accountable for the process.

• Diagnostic abilities : Industrial psychologists must construct and analyze large amounts of information and multifaceted processes.

• Proficiency assimilation : Industrial psychologists must provide more comprehensive explanations of multiple dilemmas, such as examining increasing amounts of algorithmic data ( Hecklau et al., 2016 ).

Societal Competencies

• Intercultural abilities : Industrial psychologists' ability to understand different cultures, especially when working internationally and nationally ( Ulrich, 2021 ) is also important.

• Fosters cooperation : Industrial psychologists have demonstrated the ability to successfully facilitate teamwork and cooperation in the workplace. In addition, they are analyzed for their openness and self-awareness, as well as their ability to inspire trust and respect, build relationships and bring people together ( Ulrich, 2021 ).

• Language abilities : Industrial psychologists are expected to converse and understand with international colleagues and customers.

• Communication abilities : As virtual work increases, industrial psychologists are required to have adequate virtual communication skills, as well as great listening and presentation abilities.

• Networking abilities : As a result of a highly globalized and interconnected value chain, industrial psychologists are required to take part in knowledge networks.

• Teamwork abilities : Industrial psychologists are called upon to respect team rules as teamwork and collective work on platforms increases.

• Compromising and cooperative abilities : Creating win-win scenarios in organizations with increasing project work is necessary for industrial psychologists who work alongside value chains as equal partners.

• Knowledge transfer abilities : Industrial psychologists could assist organizations in retaining knowledge. With the current demographic transformation, explicit knowledge and tacit knowledge must be exchanged.

• Leadership abilities : As responsibility increases and hierarchies flatten, every industrial psychologist becomes a leader ( Hecklau et al., 2016 ).

Personal Competencies

• Flexibility : Industrial psychologists are more independent as virtual work expands; work-task rotation requires further flexibility in their job responsibilities.

• Uncertainty tolerance : In particular, work-related change resulting from work-task rotations or reconfigurations involves enduring change for industrial psychologists.

• Continuous learning : Industrial psychologists must be willing to continue learning because of frequent work-related changes.

• Ability to work under pressure : Shorter product life cycles and shorter marketing time mean industrial psychologists need to deal with increased pressure due to shorter product life cycles.

• Sustainable mindset : Industrial psychologists represent their organizations and should contribute to sustainability initiatives ( Norouzi, 2022 ).

• Compliance : For instance, industrial psychologists are subject to more stringent rules regarding information technology security, machines, or hours of work ( Hecklau et al., 2016 ).

• Resilience : This involves the capacity of industrial psychologists to cope despite the 4IR-STARA, barriers, or limited resources. Resilient industrial psychologists are willing and able to overcome fears of the 4IR-STARA by tapping into their emotional strength.

Discussion and Practical Implications

The strategic intelligence role of industrial psychologists in the fourth industrial revolution.

Given the proposed competency model, industrial psychologists must perform a strategic intelligence role in organizations in terms of the top ten 4IR workplace trends identified in 2021 ( Stark, 2021 ).

4IR Trend #10: Virtual Learning

In 2021, the tenth most impactful trend was virtual learning, in which 4IR technology delivered instruction and facilitated more effective learning. The use of 4IR technology for enabling digital learning and gamification has been evolving for decades, along with the advancement of robust technology and algorithms; however, the global pandemic, where many were confined to their homes and were unable to attend traditional classrooms, accelerated usage and adoption across workplaces and educational institutions globally ( Mulyadi et al., 2022 ). Industrial psychologists with extensive experience in learning design, delivery, and measurement developed and implemented platforms and tools. A few examples include learning experience platforms to complement traditional learning management systems, updating learning programmes to be mobile/remote-first, incorporating behavioral economics into approaches to facilitate action, and analyzing how knowledge is retained and applied differently because of new delivery methods ( Boyle, 2021 ).

4IR Trend #9: Building Cultures of Agility and Adaptability

Various industries and locations are experiencing so much disruption in 4IR that many businesses have had to adjust their business strategies and work approaches accordingly. Some organizations reduced their workforces, while others rapidly expanded, resulting in a considerable amount of change in a short time. Many companies found it easier to navigate the change than others, and some that do not describe their organization cultures as agile and adaptive have begun to build this capability going forward. To support organizations to respond, industrial psychologists apply diagnostic tools, create playbooks, and design other interventions to help them adopt new values, change their mindsets, and develop their capabilities. By leveraging data to inform decision making and updating existing practices, industrial psychologists are also helping their organizations to increase their agility and adaptability, through strategic practices such as workforce planning, talent analytics, and talent management and development ( DeMeuse, 2021 ).

4IR Trend #8: The Changing Nature of Work

Recently, many advancements in this trend can be explained by the growing adoption of artificial intelligence, increasing digitisation of processes, increasing automation, and changing approaches to who (e.g., employees, contractors, consultants) performs the work and how, which are often determined by changes in the required skill sets. Despite its influence in many domains of technology, artificial intelligence itself lacks any theory of how humans function. In the future, industrial psychologists will play a pivotal role in integrating psychological research on job performance and individual wellbeing with cutting-edge artificial intelligence techniques. By leveraging artificial intelligence in a manner that supports individuals rather than solely focusing on organizational efficiency, it is possible to strengthen the humanistic aspects of work. Artificial intelligence should be guided and steered by industrial psychologists to make the workplace a healthier one for humans ( Sydell, 2021 ).

4IR Trend #7: Work-Life Integration

As a result of the COVID-19 pandemic, work-life integration became a key trend. The shift to work from home brought together work and other aspects of life in new ways. Adaptations must be made to take care of schooling for children, managing illnesses in family and friends and other aspects such as community involvement, wellbeing, health, and other lifestyle aspects. In addition to helping organizations understand their employees' challenges and update workplace practices, industrial psychologists can assist with stress management, workplace engagement (for instance introducing stress management tools), training, flexibility, and other important interventions ( McDermott, 2021 ).

4IR Trend #6: Team Effectiveness Across Virtual and Distributed Environments

With many workers no longer working at their offices, team effectiveness re-emerged in 2021 as a top trend. Since collaboration 4IR technology developed significantly in recent years, some organizations have become accustomed to working without being physically co-located but others are dealing with productivity challenges as leaders, managers, and team members who previously relied on physical proximity are adopting new methods of working. Industrial psychologists could provide organizations with models and training on how to respond to this trend by facilitating the alignment of resources, the facilitation of effective communication, conflict management, and other effective behaviors that foster and sustain team performance ( Curphy, 2021 ).

4IR Trend #5: Social Justice

Corporate social responsibility (CSR) programmes and organizational practices have for decades incorporated elements of social justice, ensuring that all people have equal rights and opportunities regardless of individual factors. In the United States of America, when a white police officer killed George Floyd in Minneapolis, it seemed to serve as a tipping point for many organizations integrating these programmes further into their operations. Industrial psychologists assist organizations to address these complex issues by providing advice and facilitating the identification of meaningful goals that meet the ecosystem's needs and developing road maps (including leadership commitments, employee and community involvement strategies, skill-building activities, measurement tools) to address them ( Beri, 2021 ).

4IR Trend #4: Inclusive Practices to Get, Keep and Grow Talent

An inclusive culture is a practice implemented in organizations to ensure that all people feel valued and accepted in the workplace regardless of their identities (for example, race/ethnicity, gender, sexual orientation, gender identity, disability, social class, religion). Diversity in the workplace can enhance the number of positive outcomes resulting from individual and organizational diversity. Diversity, equity, and inclusion are managed effectively when diverse talent is enthusiastic about working at an organization, can put forth their best performance, and wants to stay. Industrial psychologists are uniquely qualified to assist in this effort in several ways, including providing organizations with knowledge of inclusive practices, evaluating current practices, identifying improvement areas, designing training to support implementation, exploring the role of implicit and explicit bias in organizational processes, and designing interventions to address disparities in job attitudes across groups ( Jones, 2021 ).

4IR Trend #3: Implementing Strategies and Measuring Progress on Diversity, Equity, Inclusion, and Belongingness

In contrast to the previous trend, diversity, equity, inclusion, and belongingness programmes are being measured as their impacts emerged as a separate trend in 2021. Talent analytics capabilities are constantly evolving, which is to be expected. Progress on diversity, equity, inclusion, and belongingness initiatives, or the lack thereof, has become increasingly visible in recent years thanks to the collection of accurate and consistent data over time, and the availability of practical reporting and dashboarding tools for key stakeholders. In addition to managing large amounts of information, industrial psychologists can aid organizations in providing descriptive analysis, predictive insight, and prescriptive recommendations that will lead to increased awareness and education ( Cooley, 2021 ).

4IR Trend #2: Employee Health, Wellbeing, Wellness, and Safety

Organizations continue to focus on this trend as a top priority. The cost of benefits is increasing, and organizations are investing in ways to provide employees with stress management to help reduce the physical, mental, and emotional strain that drives the increase. Costs such as lower engagement, performance, and retention are both direct to the balance sheet and indirect to the balance sheet. As a result of COVID-19, safety has become a much greater priority for essential employees and non-essential employees; employees have been working from home and experienced greater integration between work and family. By identifying root causes of stress and designing programmes to reduce risks, industrial psychologists support organizations. In collaboration with other experts, industrial psychologists advise employers and employers' expanded workforces about implementing policies and practices that promote employee health, wellbeing, wellness, and safety ( Arvan and Fletcher, 2021 ).

4IR Trend #1: Remote Work and Flexible Working Arrangements

As the leading 4IR trend in 2021, working remotely and collaborating on flexible work arrangements dominated. While the rise of remote work has different implications for different industries, occupations, and regions, it has had a broad impact across the board for both employers and employees. Industrial psychologists can play a strategic intelligence role in guiding organizations to embrace this 4IR trend by leading them to update their culture and leadership practices. By rebuilding offices into only hot desks and communal meeting areas, strategies can be less reliant on geography, while in other cases, they need to consider the effects on different types of workers. Industrial psychologists may also assist organizations with the development of remote working policies, compensation policies, productivity measures, hiring practices, satisfaction and retention assessments, and career development strategies ( Wuerfel, 2021 ).

As an industrial psychologist with experience in 4IR, STARA contexts, the author regards himself as having played an important role in the education and training of highly qualified industrial psychologists. Students who qualify can contribute competently and ethically to strategic and operational human resources (personnel) practice, as well as people (individuals, groups, organizations) behavioral dynamics, assessment, and intervention design in organizations. A generational and culturally diverse knowledge and information society demand attention to both disruptive changes in 4IR, STARA, and evolving needs. In line with the Health Professions Council of South Africa's (HPCSA) scope of practice for industrial psychologists, and the HPCSA Minimum Standards for the Training of Industrial Psychology (February 2019), the curriculum is designed to focus on the development and application of industrial and organizational psychology domain competencies pertaining to tangible and observable human behavior-related diagnosis, design, intervention and assessment applied at the individual, group and organizational levels. To understand, modify and enhance individual, group and organizational behavior wellbeing and effectiveness ( Coetzee and Oosthuizen, 2019 ), and to enhance individual, group and organizational wellbeing, the objectives of the training include the planning, development, and application of universal, Afrocentric, and psychological paradigms, theories, models, models, constructs, and principles.

The industrial psychology profession must contribute to the development, design, and implementation of methods of inquiry that utilize specialized knowledge, skills, and technologies that are relevant to the profession's ability to respond to complex and challenging human behavior issues within a 4IR organizational context. The solutions, insights, and new knowledge that can be generated by advanced scholarship and research in the South African and African work contexts may contribute to productivity, human growth, and quality of life at work. Interns pursuing further distance education and training as prospective industrial psychologists can gain practical experience through open distance education and learning. Training and education for industrial psychologists are based on experiential learning involving the application of knowledge the article concluded with an analysis of the various ramifications of the 4IR, STARA, particularly for industrial psychologists. STARA will forever change the profession of industrial psychology, and current industrial psychologists should take this into consideration. As a result, they need to gradually become aware of the potential impacts of STARA inside their field and design strategies for how to cope with them. In an age where AI and machine learning are becoming more common, industrial psychologists can play a vital role in ensuring the effective use of information and research, assisting with data translation, and ensuring the legitimate reliability of information models and their use. By creating interventions to enable employees to adjust to AI “colleagues”, industrial psychologists could assist researchers in understanding their employees' reactions to AI. The inclusion of industrial psychologists in information technology departments will be a basic requirement for organizations to use their skills, ensuring optimal results ( SIOP Communications Department the Media Subcommittee of SIOP's Visibility Committee, 2019 ). As an opening to research and self-awareness, this new period of the 4IR could be viewed as a time of energy for industrial psychologists. Industrial psychologists play a strategic intelligence role in assisting organizations with disruptive change and development through the provision of wellness programmes to assist employees to cope with these changes ( Coetzee and Oosthuizen, 2019 ).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the author, without undue reservation.

Author Contributions

RO conceptualized and wrote the article.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: fourth industrial revolution, industrial psychologist, career, change, disruptive technology, competence, STARA, strategic intelligence

Citation: Oosthuizen RM (2022) The Fourth Industrial Revolution – Smart Technology, Artificial Intelligence, Robotics and Algorithms: Industrial Psychologists in Future Workplaces. Front. Artif. Intell. 5:913168. doi: 10.3389/frai.2022.913168

Received: 05 April 2022; Accepted: 15 June 2022; Published: 06 July 2022.

Reviewed by:

Copyright © 2022 Oosthuizen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rudolf M. Oosthuizen, oosthrm@unisa.ac.za

This article is part of the Research Topic

Impact of Digitalization on Workers' Health and Work-Life Balance

Dwelling within the fourth industrial revolution: organizational learning for new competences, processes and work cultures

Journal of Workplace Learning

ISSN : 1366-5626

Article publication date: 24 July 2021

Issue publication date: 10 January 2022

This paper aims to address the relevance and impact of the fourth industrial revolution through a theoretical and practical perspective. The authors present both the results of a literature review, highlighting the new competences required in innovative workplaces and a pivotal case, which explores challenges and skill models diffused in industry 4.0, describing the role of proper organizational learning processes in shaping new work cultures.

Design/methodology/approach

The paper aims to enhance the discussion around the 4.0 industrial revolution addressing both a theoretical framework, valorizing the existing scientific contributes and the situated knowledge, embedded in a concrete organizational context in which the fourth industrial revolution is experienced and practiced.

The findings acquired through the case study endorse what the scientific literature highlights about the impact, the new competences and the organizational learning paths. The conclusions address the agile approach to work as the more suitable way to place humans at the center of technological progress.

Research limitations/implications

The paper explores a specific organizational context, related to a high-tech multinational company, whose results illustrate the empirical evidence sustaining transformations in the working, professional and organizational cultures necessary to face the challenges of the fourth industrial revolution. The research was conducted with the managers of an international company and this a specific and limited target, even though relevant and interesting.

Practical implications

The paper connects the case with the general scenario, this study currently faces, to suggest hints and coordinates for crossing the unfolding situation and finding suitable matching between technological evolution and the development of new work and professional cultures and competences.

Social implications

Due to the acceleration that the COVID-19 has impressed to the use of digital technologies and remote connexion, the paper highlights some ambivalences that the quick evolution of the new technologies entails in relation to work and social conditions.

Originality/value

The opportunity to match both a literature analysis and an in-depth situated case study enhances the possibility to achieve a more articulated and complex view of the viral changes generated in the current context by the digitalization process.

• Competences
• Organizational learning
• Fourth industrial revolution
• Technological innovation
• Work and organizational culture

Ivaldi, S. , Scaratti, G. and Fregnan, E. (2022), "Dwelling within the fourth industrial revolution: organizational learning for new competences, processes and work cultures", Journal of Workplace Learning , Vol. 34 No. 1, pp. 1-26. https://doi.org/10.1108/JWL-07-2020-0127

Emerald Publishing Limited

Copyright © 2021, Silvia Ivaldi, Giuseppe Scaratti and Ezio Fregnan.

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

The world is facing huge changes in culture, society and economy which are direct consequences of the digital revolution, that is depicting a new dwelling place where we are challenged to live. Technologies play an essential role in the upcoming fourth industrial revolution, discussed on a global scale, as when the World Economic Forum (WEF) focused its attention on it in 2016 (WEF, 2016). This phenomenon is represented by an unprecedented level of automation and connectivity, based on artificial intelligence, big data, robotics and the internet of things (IoT). Such a modified scenario is changing our lives as social beings, citizens, consumers, professionals and practitioners inside the so-called Industry 4.0, characterized by a new conception of the manufacturing processes, decentralized and adopting systems based on the information and communications technologies ( Park, 2017 ).

Even though we are aware of the drivers of innovation (automation and connectivity), we are still far from a full understanding of the potential of this revolution in terms of both speed and extent. We can for instance take into consideration the almost unlimited possibilities of connecting billions of people by means of mobile devices, generating an unprecedented capacity for processing, archiving and accessing information ( Schwab, 2016 ).

As the first industrial revolution different phases changed our society, from rural/feudal to industrial/capitalist and then to industrial/tertiary. Automation and connectivity always played a crucial role in this process, along with the spasmodic search for increased productivity.

Many debates addressed the current situation, discussing its own features and highlighting both the advantages and risks it implies.

The first widely analyzed element is the very nature of this era and its orientation ( Park, 2017 ). Most of the worldwide economic community defines the current scenario as the fourth industrial revolution, but several established authors argue that just now we are living the first effects of the Third Industrial Revolution and soon we will experiment with its evolution ( Rifkin, 2016 ; Blinerd, 2006 ).

According to Klaus Schwab, we are going to experience a revolution and not just an evolution on the basis of three criteria: speed (due to today’s world, which is extremely heterogeneous and interconnected because of the increasingly performing technologies), range and intensity (combining different technologies the individual constantly changes at economic, corporate and social level); impact on the systems (whole systems can be transformed by such a radical change, including countries and the global society itself) ( Schwab, 2016 ).

A second element at the core of the debate on the fourth industrial revolution is the one between the so-called optimist and pessimist authors. The former group believes that in the long term the opportunities generated by new technologies will minimize the damages caused in the short term. Pessimists are convinced that we are facing a vertiginous free-fall toward the end of work and an undeniable consequent increase of inequalities at both global and intra-national levels ( MacCarthy, 2014 ).

Such first elements of discussion let many other issues emerge in the literature brings to light both concerns and opportunities related to the upcoming revolution. The main components resonating in this context include automation and connectivity again ( Schwab, 2016 ; Park, 2017 ; Prisecaru, 2016 ; Caravella and Menghini, 2018 ; Corazza, 2017 ; Blinerd, 2006 ), as well as all those technologies whose development is opening the way for progress and countless new possibilities, following an exponential growth model ( Caruso, 2017 ; Schwab, 2016 ).

The impact interests the physical area (e.g. autonomous vehicles, three-dimensional printers and advanced robotics), the digital area (e.g. IoT, platforms and IoS) and the biological area (e.g. artificial intelligence for genetics, biology and related applications).

Currently, technological innovations have strongly influenced every aspect of both economic and social life, impacting basic mechanisms as the development of the demand, as well as the accumulation of capital and the generation of employment ( Schwab, 2016 ).

Finally, the current scenario related to the COVID-19 pandemic has boosted the use and diffusion of technological devices (remote working, smart working, apps, analytics, etc.), answering the need to tackle the dramatic worldwide emergency we must face ( Carroll and Conboy, 2020 ).

Hence, the need for a deeper understanding of the challenges implied in becoming competent dwellers of the fourth industrial revolution’s scenario, specifically pointing out, in this contribution, the solicitations at stake in the organizational learning processes oriented to the achievement of new competences and work cultures.

What is the scientific contribution, moving from an interdisciplinary lens (socio-economic, managerial, work and organizational psychology fields), about the relevance and impact of the fourth industrial revolution?

What are the main implications for organizational learning processes?

What new approach to work, new competencies and cultural change need to be promoted due to the incoming technological and social scenario?

Seeking to face such questions, we will address both a theoretical framework, valorizing the existing scientific contributions through a literature review and the situated knowledge, embedded in the concrete organizational contexts, studying a specific workplace in which the fourth industrial revolution is experienced and practiced.

The paper unfolds as follows: first, we highlight the more relevant results of a literature review we made to provide a deeper exploration of the scientific contribution around the fourth industrial revolution, as a macro lens for reading the phenomenon from an interdisciplinary perspective in Section 2. Then we offer an account of the organizational learning implications that are required in this emerging work landscape, as a meso level viewpoint for acknowledging relevant shifting points in innovative workplaces in Section 3. After that we turn to a case study drawn from the field research, discussing its emblematic relevance in shaping new competences, processes and organizational cultures, as a micro-level stance for understanding the intertwined and embedded features of competence development in the emerging work environments in Section 4. We conclude by connecting the case with the general scenario we currently face, to suggest hints and coordinates for crossing the unfolding situation and finding suitable matching between technological evolution and pandemic emergency in Section 5.

2. Fourth industrial revolution in the scientific debate: a macro-level perspective

Taking into consideration the context illustrated in the introduction, a systematic literature review ( Tranfield et al. , 2003 ) has been conducted, following the Alvesson and Sandberg perspective ( Alvesson and Sandberg, 2013 ), to provide an overview of the available scientific contributions concerning the debate on the fourth industrial revolution, trying to understand orientations and relevant topics.

Mapping the contributions bringing to light the main focuses of the fourth industrial revolution;

Providing an exhaustive analysis of the selected contributions, distinguishing the main hypothesis at the basis of the current debate to investigate both its potential and challenges; and

Identifying the different perspectives adopted in literature and the different interpretations of the phenomenon.

The research process has been carried out using both databases and additional “open” sources. The considered time frame has been May 2008–May 2018. The used databases have been SCOPUS, ProQuest, JSTOR, Rivisteweb and Google Scholar, starting from some keywords to identify the potentially interesting articles for the study. The keywords used were: “fourth industrial revolution,” “industry 4.0,” “digital transformation,” “artificial intelligence” and “robot.”

A first selection phase was completed using as inclusive criteria: article peer-reviewed; with descriptions and interpretations of the fourth industrial revolution; with analysis of the impact of the digital transformation. Additional criteria to select the contributions have been that they had to belong to one of the following categories: scientific articles, documents of conferences about this issue, chapters of texts quoted more than once in the other articles. We identified the first sample of 117, among which 57 were excluded after abstract and title reading, while 60 full-text articles were assessed for eligibility as potentially interesting works, of which 29 articles have been the object of a deep qualitative analysis of their contents. A relevant turning point in this assessing process was the publication of Klaus Schwab’s book “The fourth industrial revolution” in 2016, which catalyzed the interest of the scientific community in all its implications (social, economic and organizational). The articles have been classified by year of publication, title, authors, focus and disciplinary field.

From the analysis of such contributions, we identified three leading topics : impact of the fourth industrial revolution on society as a whole; labor market and related technological unemployment; new competences for coping with the industrial revolution.

2.1 Impact on society

With relation to the impact on society, organizations and institutions, the literature analyzed tries to predict the future effects of the revolution on the different social systems. The awareness of the epochal change that we are going to live must serve to face its challenges, limiting the damage as much as possible and fully exploiting its potential ( Daemmrich, 2017 ; Makridakis, 2017 ; Schwab, 2016 ; Chung and Kim, 2016 ).

The literature review identifies both potentials [closeness and connection between people and institutions (hierarchies and bureaucracy will constitute a limit to production and diffusion of knowledge) and more aware and autonomous people and workers; more skilled and talented people] and risks [improvement of the gap due to the unequal distribution of resources and improvement of precariousness]. The potential of the new wave of technologies is to increase the level of productivity and growth but also to respond to global issues such as environmental sustainability. The risks concern the increase in social inequalities, the worsening of work conditions and technological unemployment ( Chung and Kim, 2016 ; Schwab, 2016 ; Park, 2017 ; Garrett, 2013 ).

Indeed, the continuous technological innovation takes place within a broader transformation of the economy as a whole, in an unfolding process of evolution from traditional models [global competition, mass customization, neo-liberalistic approaches in conceiving management and organizational processes ( Bondarouk and Brewster, 2016 ; Janssens and Steyaert, 2009 )], toward a development of services and new ways of sharing, circular and generative economy ( Stiegler, 2014 ; Butera, 2017 ), supported by digital technologies.

For what concerns the productive organizations, on the one hand, technologies such as artificial intelligence will most likely increase the number of automated jobs and consequently reduce the demand for work; on the other hand, the efficient functioning of new businesses will require highly qualified and talented employees. The management of talented individuals capable of implementing innovative ideas and strategies will become a real competitive advantage ( Makridakis, 2017 ). The centrality of talent requires a revision of organizational structures as flexible hierarchies, new ways to evaluate and reward performance and new strategies to attract and retain qualified personnel will become essential aspects for a successful business ( Schwab, 2016 ). Human capital and technological innovation will play the most important role in the success of companies ( Park, 2017 ), while the new employment contract will include continuing training as worker’s rights.

More in general, the digital transformation entails a revolution in the socio-cognitive models of our realities both in the individual and in the interactional and collective horizons. Regarding the social sphere, we are experiencing a real paradigm shift that involves the way we work, communicate and access information but also the way we express ourselves and spend our free time ( Schwab, 2016 ). We live perpetually connected to the network and this is paradoxically limiting communication and social relations. Hence, the need to acquire skills to dwell in a hybrid world in which it will not always be obvious to understand the nature of the interlocutors (human or artificial) and the environments (real or virtual) in which relationships are realized. Hence, also the need to rethink and redefine some typically social attitudes such as delegation, control, trust, autonomy, responsibility, dealing with the society of the future as “Internet society” ( Bakardjieva, 2005 ), “network society” ( Castells, 1996 ), “Knowledge-based society” ( Stehr, 1994 ), “cybersociety” ( Jones, 1998 ). Living in a knowledge-intensive society requires relevant learning processes at both individual and collective levels.

2.2 Labor market and technological unemployment

About the newly emerging work conditions, the great challenge we are going to face in the labor market requires an in-depth analysis of the employability of workers and the survival/growth of companies. This specific field of study focuses on the effects of the widespread implementation of new technologies on the labor market, aiming at evaluating possible consequences of the technological progress on the labor supply and demand, as well as on the workforce composition. The questions that the literature aims to answer are: will the new technologies generate widespread unemployment? Can they lead to the end of human labor? Are economic inequalities set to increase? What effect will the fourth industrial revolution have on the quality of human work that will survive it?

The publications by Brynjolfsson and McAfee “Race against the machine: how the digital revolution is accelerating innovation, driving productivity and irreversibly transforming employment and the economy” (2011) and “The second machine age” (2016), are particularly relevant as they provide valuable insights into the debate on future changes in the labor market. On the one hand, there are those who believe that the risk of computerization is overestimated (Berg et al. , 2018; Arntz et al. , 2017; David, 2015); on the other hand, there are those who state it is a realistic view of the decades to come and of the challenges we will experience ( Caravella and Menghini, 2018 ; Franzini, 2018 ; Schwab, 2016 ; Frey and Osborne, 2013 ). Many studies show that firms, which invest a lot of money in the development of their employees and in training activities incur big losses due to the lack of transfer of the new competences acquired in the workplace ( Caravella and Menghini, 2018 ; Park, 2017 ; Makridakis, 2017 ; Schwab, 2016 ; Prisecaru, 2016 ; Frey and Osborne, 2013 ).

We can highlight two opposite effects on employment described by literature: a disruptive effect, which leads to the replacement of the labor force by obliging workers to unemployment; a capitalization effect which, by increasing demand for new goods and services, leads to the creation of new jobs but also new companies and markets.

Digitized information has become the strategic resource par excellence and the network plays a crucial role in the organization of the economy and society as a whole;

The digital economy follows the double principle of increasing returns (because of positive network externalities) and marginal costs very close to zero;

New business models are emerging which, through collaboration and sharing, make it possible to take direct advantage of bilateral markets and the platform-based economy ( Schwab, 2016 ), accompanied by new competitive dynamics, dominated by the “winner takes all”;

Industry 4.0 allows “accelerated” production of customized mass goods because of the global fragmentation of value chains, the networking of production capacities and the overcoming of borders between producers, sellers and consumers on the one hand and between industry and services on the other; and

The cause-effect link between technological innovation and productivity has not yet been clearly established, as it is conditioned by the effective implementation of technological innovations at the social level and by organizational changes by companies.

From Caruso’s study, it emerges that all those transformations often referred to as the “fourth industrial revolution” have not so far satisfied any of the promises/hopes they have raised. Today the organization of work is no longer horizontal if not partially, workers do not seem to have obtained greater decision-making power and autonomy and work has only become more creative for a sub-fraction of highly skilled workers. On the other hand, work has become more precarious, linked to stricter standards and controls and with a significant weakening of the distinction between “working time” and “free time.” However, technological innovation is not something external to society, which is, on the contrary, its main generator and promoter. Today, due to the countless variables involved and the exponential rate of growth, it is very difficult to accurately predict the effects of the fourth industrial revolution ( Morrar et al. , 2017 ). Awareness of the epochal change that we are willing to experience must serve to face its challenges by limiting damage as much as possible and exploiting its potential to the full ( Daemmrich, 2017 ; Makridakis, 2017 ; Schwab, 2016 ; Chung and Kim, 2016 ). The technology that characterizes industry 4.0 can only reach its real potential in combination with social innovation. To seize the vast opportunities offered by the industrial revolution, technical and social innovations must coexist under the same “sustainability” roof ( Morrar et al. , 2017 ).

At stake is the focus on the development of transversal competences and the interaction between humans and machines to improve the sustainable dimensions of a production system. It is necessary that the implementation of new technologies is primarily oriented toward social and environmental sustainability ( Morrar et al. , 2017 ; Butera, 2017 ; Peters, 2017 ; Pak, 2017; Prisecaru, 2016 ; Romero et al. , 2016 ) and not to the economic interests of a few, who would lead to an increase in inequalities and/or further environmental damage. Linking new technologies and sustainability entails a relevant investment in organizational learning, seeking to shape the socio-material conditions suitable for such a key issue.

2.3 New competences to dwell within the digital revolution

Economic challenges: increasing globalization (intercultural skills, language skills, flexibility over time, networking skills and process understanding), increasing the need for innovation (entrepreneurial thinking, creativity, problem-solving, work under pressure, cutting-edge knowledge, technical skills, research skills and understanding of processes), demand for greater service orientation (conflict resolution, communication skills, knowing how to reach a compromise and networking skills), the need for cooperative and collaborative work (ability to work as a team, communication skills and networking skills);

Social challenges: demographic and social value change (ability to transfer knowledge, tolerance of ambiguity, flexibility in time and place of work and leadership skills), increased virtual work (flexibility related to time and place of work, technological skills, multimedia skills and understanding of IT security), the complexity of processes (technical skills, understanding of processes, motivation to learn, ambiguity tolerance, decision-making, problem-solving and analytical capabilities);

Technological challenges: exponential growth of technologies and data utilization (technical capabilities, analytical capabilities, efficiency in working with data, coding capabilities, understanding of IT security and compliance), creating collaborative work on platforms (ability to work in teams, virtual communication skills, media skills, understanding of IT security and ability to be collaborative);

Environmental challenges: climate change and resource scarcity (sustainable mentality, motivation to protect the environment and creativity to develop new sustainable solutions); and

Political and legal challenges: standardization (technical capabilities, coding and understanding of processes), data security and privacy (understanding of IT security and compliance).

Technical skills: state-of-the-art knowledge, technical skills, process understanding, media skills, coding skills and understanding of IT security.

Methodological skills: creativity, entrepreneurial thinking, problem-solving, conflict resolution skills, decision-making, analytical skills, research skills and efficiency orientation.

Social skills: intercultural skills, language skills, communication skills, networking skills, teamwork skills, ability to compromise and cooperate, knowledge transfer skills, leadership skills.

Personal skills: flexibility, ambiguity tolerance, motivation to learn, ability to work under pressure, sustainable mindset and compliance.

Within this framework, learning and growth of competences become two of the crucial and prior issues for enhancing educational policies and reforms such as those relating to the European Reference Framework of Key Competences for Lifelong Learning, ( https://ec.europa.eu/education/education-in-the-eu/council-recommendation-on-key-competences-for-lifelong-learning_en ) , which defines the competences of each European citizen needs to achieve personal fulfillment and development, employment, social inclusion and active citizenship. The lifelong learning perspective entails not only political initiatives at the macro level but also strategies and interventions to guarantee that individuals may access economic opportunities, being competitive in the new world of work, shifting the attention at both meso- and micro-level implications for their fulfillment. Global workforce needs to change its professional path because of the changes that digitalization, automation and artificial intelligence progress are bringing to the world of work. The type of skills required by companies has changed, with profound implications for the career paths that individuals will have to pursue. Therefore, it is spreading the need to develop processes of learning new skills (reskilling), so that you can do a different job or train people to do a job differently. The new scenario that emerges on the horizon is changing the contribution and the ways of creating value that human work will provide to organizations and the impact on workers is greater than ever before.

To sum up, the macro lens related to the three main analyzed topics, we can highlight as a transversal feature: the relevance of learning processes to cope with talented resources, the innovative approaches to managerial and organizational dimensions, the new competences and capabilities, the emerging digital challenges delivered by the fourth industrial revolution.

Hence, the need to acquire skills to dwell in a hybrid world, characterized as a knowledge-intensive society, linking new technological opportunities with a multifaceted concern for sustainability.

It becomes, therefore, evident how training and learning to develop innovative competences represent an essential response to the growing challenges impacting contemporary organizations, seizing the opportunities generated by technological innovation. In the next chapter, we address the organizational learning processes oriented to the achievement of new competences and work cultures.

3. Organizational learning for new competences: a meso level viewpoint

To face constantly transforming operative environments, a new approach is required in conceiving organizations, management and change, enhancing active learning paths and trajectories, as well as seeking higher levels of adaptive knowledge transfer.

Billett (2000 , 2001 , 2004, 2020 ) claims for making effective learning environments out of workplaces, developing guidelines for the acquisition of vocational knowledge through participation in everyday work activities.

Gherardi (2009a) argues that organizational practices have become the loci of knowing, organizing and learning, due to the practice turning point in studies on learning and knowing in organizations ( Schatzki et al. , 2001 ). The adoption of a practice lens ( Gherardi, 2009b ) entails a critical epistemological stance that pertains to an innovative cultural climate, encompassing a vast array of contributions on multiple issues such as activity system, a community of practice, knowledge, learning, situated practice, use of technologies ( Engeström,1987 ; Brown and Duguid, 1991 ; Lave and Wenger, 1991 ; Blackler, 1995 ; Easterby-Smith et al. , 1998 ; Clegg and Hardy, 1996 ; Suchman, 1987 ; Cook and Brown, 1999 ; Ciborra, 2006 ; Orlikowski, 2000 , 2002 , 2007 ).

In such a perspective of “practice as the site of learning” ( Nicolini, 2011 , 2013 ), organizational learning is conceived as an unfolding social process of becoming a competent member of a workgroup or community ( Wenger, 1998 ), acknowledging, negotiating and adopting rules, roles, languages, division of labor, tools, use of artifacts in a specific workplace context. Knowledge is conceived as socially shaped, collectively shared, distributed and circulating through socio-material dimensions (conversations, discourses, practices, doing), dealing with multiple ways of working, knowing, innovating and organizing: a texture ( Gherardi, 2006 ) of material and immaterial aspects, through which practitioners shape and reshape their system of activity every day, consolidating but also changing their practice and objects, facing internal and external pressures.

The transformation of work as an impact of the 4.0 industrial revolution, accelerated by the pandemic scenario, triggers and challenges organizations to learn with and from their members, developing a highly reactive culture to internal and external stimuli and recreating a suitable climate for the diffusion of knowledge. What is asked is the dare to leap a strict hierarchical structure of teaching and control (often seen and pursued as a managerial reassuring comfort zone), spreading the circulation of knowledge, and therefore the organizational learning. Inside what is known as the knowledge-intensive firm, it is important to grant more responsibility and autonomy to workers to generate continual learning and organizational improvement. Indeed, to unlock the potential of industry 4.0, organizations need to enhance their culture, integrated activities and structure ( Lu, 2017 ; Romero et al. , 2016 ), dealing with organizational learning processes oriented to the achievement of new competences and work cultures.

As historical theoretical models highlighted ( Lawrence and Lorsch, 1986 ; Hambrick, 1983 ; Lawrence and Dyer, 1983 ; Thompson, 1967 ; Barnard, 1938 ), in such a challenging context the organizations must survive and grow in the long term. To achieve this objective, contemporary organizations ask their employees to work in a more flexible and fast way, also due to the technological progress impacting on the complexity and dynamicity of their working activity ( Lu, 2017 ; Romero et al. , 2016 ; Salas and Cannon-Bowers, 2001 ; Ford and Fisher, 1996 ).

Learning, both individually and collectively, is, therefore, one of the most important leverages that organizations must use to obtain important competitive advantages. For an organization, it is essential to learn internally, by means of optimal management of the knowledge possessed by individuals or other resources, as well as from the external environment. Today, more than ever, it is strategic for an enterprise to adopt an effective culture of learning, facing the constant changes happening in social and business contexts, even anticipating them if possible: the issue of nurturing processes of organizational learning entails both initiatives of formal and institutional training and the valorization of available knowledge, embedded in innovative practices and developed day by day through the circulation, consolidation and change of habits, routines, new ways of coping with the internal and external solicitations. Communicating the crucial role of learning to their employees is essential for organizations, implementing adequate training activities to empower and guide its workforce toward objectives of competence development and transfer.

During the past decades, in the effort of providing the employees with the necessary knowledge and competences to face the modern context characterized by self-directed dynamic performances, it has become increasingly common to delegate responsibilities and decisions related to learning ( Warr and Bunce, 1995 ). Organizational learning becomes a learner-centered approach ( Bell et al. , 2017 ; American Society for Training Development, 2015 ), with a growing interest in active learning, whose aim is to transfer competences by means of experience instead of learning a set of top-down taught information ( Brown and Duguid, 1991 ). Hence, an emphasis on the potential of technology-based training, informal learning and community of practice for developing knowledge and skills of the employees.

Hardy et al. (2019) claim for managing exploration (knowledge expansion and innovation) – exploitation (knowledge refinement) trade-offs as a crucial point in modern, learner-centric, dynamic learning and development contexts.

The higher the information-knowledge gap, related to what learners want or need to know/be able to do (e.g. due to technological innovation pressure), the greater the attention that will be addressed to the explorative path of new knowledge; the lower the information-knowledge gap, the greater the investment that will be made to develop, consolidate and disseminate existing and already in use knowledge and competences.

Achieving a good balance between learning efforts for enhancing the use of the available knowledge (exploitation) and the investment in generating innovative knowledge (exploration), facing the uncertainty the organizations must cope with, is strongly related to organizational climate and cultural support to a proper and suitable learning environment.

In this sense, furthermore, the new technologies can become, if adequately implemented, an important tool for the active participation of learners in learning activities. The technological potential for learning has to be explored and taken into consideration seeking to activate organizational learning processes ( Sitzmann and Weinhardt, 2018 ).

In general, strategies that involve participants in a combination of exploration and exploitation lead to effective learning, while strategies that lack this type of involvement or excessively emphasize one activity over the other, are less effective.

All that said, organizational learning cannot be considered the sum of learning experiences of all workforce members; the challenge for dwelling in a competitive and evolving global context is to adopt a reactive and innovative culture, promoting effective paths for the shaping and sharing of knowledge.

Recruiting and gathering talented and competent individuals is not enough, neither it is just encouraging interaction.

a strong revision of the traditional approach in conceiving the managerial function and in achieving new competences and tools for changing and aligning strategies and activities to these new labor features ( Fregnan et al. , 2020 );

to identify and develop the skills necessary for the workforce of the future, as one of the greatest challenges for organizations in this transition phase;

a strong and diffused learning culture that allows constant updating of the skills of the employees, with specific regard to the impact of the fourth industrial revolution on workers’ activities;

exploring new learning opportunities and tools; and

developing the so-called “soft skills,” as peculiarly human abilities, which represent the great qualitative difference between man and machine, enhancing a sustainable hybrid production system.

As a consequence of the macro-level solicitations, at the meso level new organizational, professional and work cultures are the key object to be shaped, nurtured, developed and shared, dealing with disruptive changes, transforming them into opportunities for growth and positive evolution ( Brown and Duguid, 1991 ). The relevance attributed to situated, embedded and circulating knowledge, related to the way practitioners conceive and use new technologies ( Orlikowski, 2000 ), conveys the possibility of an organizational learning approach as a suitable and sustainable expansive learning process ( Engeström, 2001 ), going through and beyond resistances, turbulence, criticalities and existing contradictions.

However, the intention to create new knowledge practices and achieve a good balance between digital and physical, constraints and discretion, work and family life, is not straightforward: there is the need to get close to concrete organizational contexts, bridging theory and practice and seeking to understand how the reception of the 4.0 industrial revolution implications is rooted in practice. In the next paragraph, we address a micro-level analysis of how a high-tech company is tackling the problem to prompt new competences through organizational learning leverage.

4. The Comau HUMANufacturing: a micro-level analysis

The impact of the fourth industrial revolution on organizations and social systems, on the labor market and on workers’ skills, highlights the importance of facing the continuous changes enabled by new technologies. Research and studies point out the connection between effective learning cultures ( Plummans et al. , 2017 ; Choi and Jacobs, 2011 ; Yoon et al. , 2010 ), knowledge management and dissemination (Davenport, 2015), as well as an active approach to training paths ( Bell and Kozlowski, 2008 ; Sitzmann and Weinhardt, 2018 ).

Hence, the opportunity to explore a concrete organizational context for deepening the tensions between opportunities and risks, willingness to learn and fear of technologies unemployment, new connections between subjects and work, with the purpose to enhance our understanding of the relationship between human beings and machines based on nowadays technologies.

The choice of assuming a pivotal case, albeit not exclusive, to explore approaches, practices, skills and strategies, allows to point out how a company concretely embraces the potential of the fourth industrial revolution, also highlighting criticalities and problems of such a change. Studying the situational uniqueness of a specific context may provide analytical refinement of what is currently known, addressing the epistemic significance of the particular ( Tsoukas, 1989 , 2009 ) and enhancing the possibility to enrich the general concepts related to the issue at hand ( Scaratti and Ivaldi, 2021 ).

The research project has been conducted within Comau, an important Italian multinational company integrated with 20 subsidiaries, based in Turin and part of the FCA Group. Comau develops and implements automation processes, solutions, production services and it is specialized in welding robots. The company is working in 32 locations around the world, divided into 4 main geographic regions: North America, South America, Asia and Europe. Crossed to these regions there are three main business units: robotics, which deals with the design and production of robots traditionally for industrial use; the automation system, which deals with the design of the production lines within which robots are typically inserted; and the powertrain, which is the unit dedicated to the production of machine tools.

Comau is made up of 12,600 employees and has started important international training collaborations (10 international training partners). All the company’s activities are strictly connected to innovation.

Because of the combination of advanced technological know-how and its long-term experience, the organization is stimulated to undertake a process of constant innovation that gives life to new products, advanced technologies and an innovative factory concept that optimizes the automation oriented to man and machine.

The company’s vision, facing the challenges of a constantly evolving market, is summarized by the concept of HUMANufacturing, like a weave between the fourth industrial revolution and the possibility to place humans at the center, as well as to remark the role of technology as a useful tool to help satisfy human needs. Comau is in fact committed to implementing technology-enabled solutions for Industry 4.0 such as innovative real-time data transfer techniques, virtual reality and the latest generation of wearable devices.

being engaged in continuous research and open innovation, today Comau seeks to integrate the 4.0 paradigm into its organizational culture;

learning has a central role within the company, as the numerous international training partnerships demonstrate;

the company faces an important global presence that allows being highly reactive to the different environments in which it is inserted;

the corporate vision aims to develop the human-machine relationship as a core value of the HUMANufacturing approach (declined in the adoption of Cobots and exoskeletons); and

finally, the company commitment is strongly oriented to promote knowledge transfer, transmitting the 4.0 culture to new generations.

Two were the principal aims in studying the Comau case: the first refers to the actual experience of the organizational members facing the changes and the challenges they have to cope with; the second is related to the company approach seeking to promote organizational learning.

The professional history of employees, their interpretation of their role in the company and the changes observed in their working activities;

The new approaches to work, the role of technology and the main technologies adopted today within the company;

The fundamental skills within the company;

The role of learning, as well as the knowledge diffusion and management to face the stimuli and continuous changes in the operating environment; and

The organizational culture and the changes needed to effectively exploit the potential of the fourth industrial revolution.

Dealing with the actual experience and facing the meaning people give to their personal and professional trajectory, we adopted a qualitative methodological approach, following the “grounded theory” guidelines ( Glaser and Strauss, 1967 ; Charmaz and Belgrave, 2007 ). The research was carried out through six semi-structured individual interviews and two focus groups, involving company employees. The interviewees were identified on the basis of the availability of respondents, among a sample proposed by the human resource (HR) management function on the basis of their key role within the business change process (agents of change) and the time spent working for the company (changes observation); the focus groups’ participants were invited asking to confirm via e-mail their availability, on the basis of their participation to the company specializing master, their young age (Generation Y) and their recent entry into the company. Each participant received an informative sheet concerning the respect of both their privacy and anonymity.

The intention was to detect knowledge about the organizational learning process both from senior staff, involving internal managers as carriers of project purposes and from the target of the learning process, considering their interpretation of the learning path experienced to achieve new competences. Dealing with the former, we gathered knowledge about the learning projects at stake, while the latter pointed out their involvement in a two-year executive master (with a pause of one week per month). The first year of the masters was related to academic disciplinary fields, the second one was focused on a learning path immersion within the Comau organization, acknowledging the emerging innovative culture through situated project works with other employees.

For both the interviews and the focus group activities, being semi-structured, it was provided a draft containing the general questions to be asked to the interlocutors, assuming a conversational orientation giving space to unfolding, discourse, comments, considerations. The draft was mainly used to identify the topics considered essential for the purposes of the research.

Can you tell me who are you? What is your role within Comau? (when you arrived, why, with what objectives). If you have been working as a manager or you have been with Comau for a few years, have you been able to observe changes in your job or role?

Nowadays we talk about the fourth industrial revolution, in your opinion, what are the most significant changes it is generating in the world of work?

Thinking about the Comau context, what are the knowledge, skills and activities most requested to workers?

How could organizations help workers to be prepared for today’s world of work? What does Comau do in this sense?

How is the fourth industrial revolution being carried out internally? What do you think are the drivers for the spread of an innovative culture capable of integrating the profound changes we are experiencing?

What are the learning processes that are recommended/proposed to your employees and on which skills do they focus in particular?

What does it mean to be a worker today? What do you think they need most? What are the required skills and knowledge and how should learning paths be structured? According to which drivers?

What is the role of technology today? How is technology changing the way people relate to work?

1 st Step: Presentation

Round table presentation of the participants in the focus group (who they are, how long they have been with Comau, what role they play).

2 nd Step: Investigation of the changes of the fourth industrial revolution

Nowadays we talk about the fourth industrial revolution, what are the most significant changes it is generating in the world of work?

What does it mean to you being a manager today? What differences do you find, if compared to the past?

What do you think are the most important knowledge and skills for workers and managers today?

What should an organization do to encourage learning and promotion of the culture of the fourth industrial revolution? What role should managers play?

3 rd Step: Focus on the specializing master experience

What adjectives/words would you use to describe the specializing master experience?

What are the drivers that were transmitted to you within the specializing master organized by the Comau Academy?

What were the situations of the specializing master that most favored your learning?

If we were to do a Comau SWOT analysis about the promotion of learning, what do you think are its strengths, weaknesses, constraints and opportunities?

The following six employees were interviewed: A- head of HR recruiting and of the “digital initiatives platform” cross-sector entity (20 years within the group); B- digital team manager (33 years within the group); C- digital team manager and head of funded projects (22 years within the group); D- innovation manager (7 years within the group); E- training and e-service manager (18 years within the group); F- business development manager at the corporate level and in the robotics business unit (30 years within the group).

For the focus groups, 16 people were randomly invited among the participants at the specializing master, focusing on their belonging to the generation Y (born between 1980 and 1999) and seeking to explore their learning experience as young workers who have joined the company a little time before.

Having recently participated in a learning path and having recently joined the company (as well as the world of work), their contribution could have been particularly useful in understanding the learning needs perceived by workers and the alignment of the activities offered by the company to the needs of its own employees. The focus groups were, therefore, essential to understanding how workers were involved in the company and to discuss their expectations with them.

4.1 Findings

The interviews and group discussions have been audio-recorded, transcribed and carefully analyzed, adopting both a phenomenological and semiotic perspective ( Mininni and Manuti, 2017 ), as well as a ricoeurian hermeneutic orientation ( Bartunek and Louis, 1996 ; Cunliffe and Locke, 2019 ).

the enhancement of new approaches to work (related to the points of interest I and II);

the introduction of new competences (related to the point of interest III); and

the promotion of a cultural change (related to the points of interest IV and V).

Regarding the new approaches to work, the most important required change refers to the shifting from a logic of execution to a logic of improvement of the working processes.

Comau is now organizing teams and activities into projects, instead of following a functional structure:

“There are two types of changes: changes of a technical nature and changes of a cultural, managerial or rather general type. From a technical point of view, all our products must be equipped with options that allow data reading or remote management. From a purely cultural and social point of view, new professions are certainly being created and others are probably disappearing” (D1).

“We are moving from a product culture to a service culture. This is a big change and not only at an industrial level. The machines that are rented today in the cities constitute the acquisition of a service and not a product. A similar thing is happening also for the machine tools” (F1).

This business activities organization simplifies the sharing of competences and influences the approach to career. The choices linked to the professional career of workers are increasingly self-directed, instead of depending on a dedicated institution:

“This clearly has an impact on people’s careers too, how they see their work, etc. […] it’s all very different and seen from the outside it can seem very confusing, but seen from the inside it doesn’t. The effort is not to design an organization, but it is always to be clear in what you do and what you don’t do. Because again, you don’t have a job description, you rather have a skills profile that you make available to what there is to do and what you like to do” (A1).

“The approach to career is also different because there is no longer a staff body that, together with your boss, designs your path; of course, they do it, but on macro trends. What you will do the next day must also be manifested by yourself and this is a big change” (Focus group, I, 1).

A second feature emerging from the interviews is that workers choose whether to participate in a project because of their competencies and their will to do it. The result is a “nebula organization” that seen from the outside can seem pretty much confused, but internally is well organized because everybody knows who the supervisor is:

“Shaping a very fluid work organization with clear objectives is in fact something that never ends. One piece of the project ends, but another one opens up and you have to start all over again, re-explain it, communicate it again within the teams, outside the teams and within the organization. It is always in the process of becoming […] more than a hierarchical organization, it is a nebulous interlocking organization” (E1).

“Assigning activities to a person is based on the skills he/she possesses and what he/she desires. It’s a very different thing from the classic way of working, where a person has a role and has a job description and does that until they change his/her role if they change it. These teams are extremely permeable teams. The teams are organized and everyone knows who his/her boss is, but someone who writes software can also work on the commercial proposal to the client because he/she has the skills to do it and wants to do it. He/she can, thus, contribute with his/her own skills and get help for those he/she does not have” (C1).

“I have been here for two years and in this period of time, my work has changed a lot. We observe many changes at the level of technical solutions that are adopted to design a line from scratch. An example is AGVs, which are a technology that was inconceivable to install on lines up to 10 years ago. Today the idea of no longer having lines that are real straight lines, but that is much more flexible, certainly facilitates our work in many situations, allowing much more flexibility to solutions” (Focus group, I, 2).

A third aspect is that collaboration between humans and machines is becoming essential for companies. It is important to underline that machines are becoming intuitive to use because they are designed to communicate like humans; differently from the past, when humans had to adapt to machines (acquiring specific skills and knowledge) to use certain tools. The adopted direction, as the founding assumption of the HUMANufacturing culture, is the ennobling of human work and the removal from repetitive and alienating activities. Workers are now paid to improve processes and not just to execute them:

“Technology must be functional to our needs as human beings. It will not replace us because there are things that cannot be replaced and, above all, we do not want it to happen” (B1).

“Moving a small bottle of water is not a human competence. Understanding where it is best to move it, that is a human skill. It has been occurring a big change in the interpretation and approach to work: from the execution of processes to the improvement of processes” (B2).

“I believe that the technology that most affects human work within the 4.0 paradigm is represented by collaborative robots. I believe they can make a difference. Staying on the ‘site’ I’ve seen how they affect various aspects of human activity such as safety in work environments characterized by the presence of Robots” (Focus group, II, 4).

The transformation of the working approach is not taken for granted and also entails problems and difficulties to be handled:

“The inclusion of suppliers relationship management was disruptive from all points of view […] Let’s say that the way of working has changed and had to lead to a speeding up of all processes and greater flexibility of individuals, but it requires effort because it takes time and people need to understand the potential to lighten the work that comes with it […]” (F 2).

“In general, it is increasingly difficult to separate personal life from what is working life. This is because we are increasingly connected […] Unfortunately, I read e-mails at all hours. It is always going more and more toward this direction” (Focus group, II, 3).

About the introduction of new skills and competencies, the participants state that technical skills remain essential in the industrial sector but even out of it if we think about the pervasiveness of technology in today’s human experience. Such skills are useful to use certain tools and to understand their potential:

“In the world of work, industry 4.0 gave me work, in the sense that I am a ‘data scientist’ and this figure was born and raised because of industry 4.0. It is becoming a widespread figure even if we will discover its actual usefulness just in a while” (Focus group, II, 5).

“In the plants, we begin to see the first workers who work wearing a watch and no longer using tools such as sheets of paper. Today these figures use tablets, smartphones, watches and soon will use the voice. Let’s say that there is a progressive change even for these professional figures because of the use of increasingly sophisticated technologies and related competences” (F3).

In addition, many participants highlighted the necessity of figures with transversal skills and broad horizontal culture, allowing them to have an overview of the different activities:

“The real novelty is precisely the introduction of people who are able to extract value from the data collected and people who are able to get the data to these systems by understanding what type of sensors to use and where to put them” (Focus group, I,6).

“The ability to collaborate or team working is fundamental. More and more there are very different skills that acquire importance […] it becomes more and more difficult for a person to have the necessary knowledge to complete a job […]” (A2).

“It is clear that soft skills such as problem-solving, project management, teamwork and flexibility are all strictly necessary. Especially if you get to cover managerial roles and enter middle management. An individual who does not know how to work in a group would not know how to work in a company that sees groups interconnected according to a logic of platform, in which they all work together to achieve the same goal. The other project management skills are equally fundamental. Today almost all activities are organized by projects, so knowing how to work and organize oneself by projects, finishing activity calendars, finishing the progress of the work control etc. […]” (Focus group, I, 5).

Finally, soft skills are increasingly important for companies. For example, the dynamicity of operative environments and the high level of specialization of workers underline the importance of flexibility and ability to collaborate, as in the following quote:

“[…] the reason why Comau hired us is precisely that of contaminating with our flexibility the others who have instead the technical skills deriving from a more consolidated experience. We had to transfer our ‘less technical’ skills, to put it in simplistic terms, to those who have been here for several years, exploiting our adaptability and flexibility” (Focus Group, II, 7).

The achievement of new competences is not straightforward either and some criticalities emerge:

“At the moment in Comau, there are different approaches between people: those who manage the traditional business in a more traditional way and those who manage the most innovative business in a more innovative way. Innovative means a lot of things. First, knowing how to use tools that did not exist until 10 years ago. I refer in particular to working on a digital platform or working on Google platforms, where everything is shared and there is nothing local […] you need to know how to work beyond space” (C2).

“There is not a method to validate the software yet. At the management level, there is still no preparation for software development because there are methods/standards that are used within software engineering but here they have not been implemented yet” (F3).

“[…] a discourse of risks exists […] We may be facing critical issues and problems never faced before and given that, the experience significantly affects our work, change can be seen as too high a risk” (Focus group, I, 7).

“Access to new skills can be seen as a limit by those who have been in this job for a long time or who have created their own comfort zone and do not want to leave it. I don’t think it’s a limit for us, on the contrary, I think it’s an opportunity” (Focus group, I, 4).

“There is not enough communication, and therefore the competences related to the fourth industrial revolution are not shared between the different business units” (E2).

The third dimension is related to the promotion of cultural change. Comau, besides the learning activities, is adopting techniques such as job rotation and the creation of inter-generational and inter-functional teams. Such paths can help workers to gain an overview of the different activities and ease the coexistence of different approaches within the organization. Moreover, the company is creating diffuse connections among people, to boost the internal diffusion of knowledge and with external realities through partnerships, to seek the competencies not yet achieved.

To change the processes can be hard work and can take months, but to change the culture of a company is even a bigger challenge because it is strictly rooted within the company history, values and activities, as well as within its members’ background:

“Certainly, it is not an easy thing since you have to clash with practices that have always existed. However, Comau is entering industry 4.0 and is changing the processes, and therefore the heart and the engine of the company. For the automation system, over the last year, the processes have been retouched and revised from all points of view. Our organization is changing and has changed a few months ago according to this new vision that the company has acquired” (B3).

“It is difficult to interpret what a customer wants because it is a myth that the customer knows what he wants. There are latent needs that not even market analysis is able to capture and that you have to be good at interpreting. There is a world that is so dynamic and liquid that it is difficult to understand it. I don’t think there is resistance, but I believe that being confused by a thousand things, we find it hard to find the right path” (Focus group, II. 8).

“Some drivers can be seen as the backbone of our change. The first is open-mindedness, and therefore the ability to look beyond one’s habits and patterns. The second is accountability, that is, taking risks at all levels of the organization because when certainties fail, you need to know how to interpret new environments. A third could be the opening of vision, in the sense that now even a classic industrial company like ours can no longer avoid looking systematically outside of itself. Because resources and skills are shared. You can no longer think about drawing your own path without systematically look around. The last driver I would like to point out is the customer, both the one who buys and the internal one. You are much more than before compared to people close to you with expectations, whether they are your employees, bosses or colleagues and who are used to express themselves also due to the fact that we are now connected. In the relationship with the employee, it is now the employee himself who tells me what he needs and what his expectations are. So, hyper-connection is another aspect that you cannot ignore because we are now connected” (E3).

Comau, to deal with this kind of change, instead of imposing it, has chosen an interesting way: the strong involvement of people as first promoters and authors of organizational change:

“[…] to adopt the exoskeleton, Comau selected key operators on the basis of certain features (potential change agents) and proposed them a set of technologies among which they picked the exoskeleton as the best tool to improve their activities. Then these operators participated in the whole design phase till the actual implementation. Their colleagues observing them immediately understood the potential of such technologies and started using them without resistances […]” (Focus group, I, 5).

“The way in which Comau is spreading this new culture is by involving people and there is no better way. You must involve people so that they begin to use these technologies and methodologies little by little. The same people who begin to use them become agents of changing themselves and begin to contaminate others until a complete diffusion of these new methodologies and technologies” (B4).

“The reason why they hired us and inserted us like crazy cells within the company is precisely to contaminate with our flexibility the others who instead have the skills of those with a more consolidated experience. It’s a bit like a virus that starts from a small group of people and then spreads. There is a healthy bacterium that is carried by some healthy carriers until it spreads to all the people within the company” (Focus group, II, 7).

“I take people who are young, not so much from the age point of view, but more from an intellectual point of view and who are, therefore, led to experimenting and I bring them to use new processes and technologies. These, in turn, become agents of change, so that people who are less inclined to accept such changes can see and follow them by imitation” (A3).

“Certainly, with inter-generational teams and inter-functional teams this type of culture can spread and we are observing it. For example, when we work on the proposal phase, we do it in close contact with all the other business units” (B5).

To govern the learning processes aimed at promoting, developing and disseminating the HUMANufacturing culture, Comau has set up an internal academy, with the aim of creating and monitoring multiple training and learning initiatives, in partnership with various international stakeholders.

Seeking to sum up the most relevant results emerging from the qualitative inquiry, we can underline that in Comau the new approach to work is based on specific processes and structures, in which acceleration and simplification, project-based organization (inter-functional and inter-generational teams), open innovation and tuning on strategic goals coexist, as the metaphor of the nebulous interlocking organization (E1) highlighted. The representation of the fourth industrial revolution and its implications concerns the enabling technologies implementation within industrial environments, based on a cultural transformation. This entails not only the spread of new technologies and machines, rather a rooted in-practice use of innovative technology by the practitioners, acquiring the necessary skills to master and fully understand it ( Bondarouk and Brewster, 2016 ; Ivaldi and Scaratti, 2020 ).

In relation to the development of new competences, Comau, as the qualitative data point out, emphasizes the relevance of both transversal skills (from execution to entrepreneurship) and digital capabilities (for the interaction between humans and machines). At stake are professional movements from knowledge accumulation to empowerment, toward a more problem-solving orientation and the active participation in practical and sense-making processes.

Concerning the cultural change, Comau promotes a HUMANufacturing approach, in which listening to the practical knowledge, responsibility toward new generations, orientation toward clients and giving value to diversity as a resource constitute the core values of a high-tech company focused on the relevance of organizational members and the sustainable relationship between persons and technology.

Albeit emblematic, the Comau case cannot be mechanically replicated, due to its uniqueness and peculiar specificity compared to other organizational contexts involved in the challenge to cope with the digital revolution. Anyway, it conveys some transversal issues that must be addressed in multiple workplace situations faced with the pressure of technological innovation.

(1) Individual

(2) Relational

(3) Organizational

related to the embedded procedures to be questioned or contested and the fear of mistakes or about tackling with consolidated powers. The challenge is the possibility to achieve a different managerial approach, coping with the unexpected and the complexity of internal and external organizational environments.

the importance of a strong alliance between top management and the engagement of key figures (middle managers, young generations) as ambassadors for the creation of a new culture;

the promotion of a diffuse awareness concerning the value of adopted technologies, improving participation, the coexistence of different approaches and a diffused mindset of managing the unexpected;

the involvement of employees at all levels in projects and events that give concrete evidence for the company’s interpretation of the fourth industrial revolution, so that they begin to use these new technologies and methodologies little by little, becoming agents of changing themselves;

the role played by institutional artifacts (in the Comau case, the Academy) and learning processes to spread the new culture; and

the care of paradigm-shifting, widespread contamination and sharing, creation of accessible memories (report, internal documents […]).

As a final result, the findings acquired through the study of the Comau case can support and endorse what the scientific literature highlights about the impact, the new competences and the learning paths solicited by the emergence of the fourth industrial revolution: shifting from a logic of execution to a logic of improvement entails a new approach to work, a good enough balance between technical and social competences and the development of innovative work, professional and organizational cultures.

Such a cultural change is not taken for granted and must be accompanied through an organizational learning process, enhancing activities engaged in transformation efforts and promoting multiparty encounters, discussions and debates. This learning process conveys, in turn, the need to cope with tensions and contradictions people face in struggling with persistent problems and challenges in their workplace walk ( Ivaldi and Scaratti, 2016 , 2020; Scaratti et al. , 2017 ). Assuming that the tension of change and future-orientation also implies material and immaterial dimensions, as people engaged in nowadays organizational contexts are asked to explore processes of learning from the fields, connecting action and thought, as well as trying to open new visions not yet available for transforming and improving their daily practices.

5. Conclusions

Aiming to enhance the debate around the fourth industrial revolution, the paper addressed questions related to its relevance and impact, to the implications for organizational learning processes and to the development of new approaches to work, new competences and cultural change.

As highlighted by the literature review, the fourth industrial revolution yields an ambivalence in the introduction of technology, identifying both potentials and risks, respectively, related to the opportunity of social growth on the one hand and of technological unemployment and worse work conditions on the other hand. As sustainability is the key to balancing the strengths and threats of the fourth industrial revolution, that can be achieved if there is a strong investment in the promotion of organizational learning. A learning process in which the experience and practical knowledge of people represent important resources for the introduction, the development and the integration of innovative technologies, matching both knowledge exploration and exploitation.

Managing and engaging people in such a process of expansive learning, as highlighted in the Comau case study, can emblematically express the challenge of the current organizational scenarios characterized by meaninglessness and uncertainty, in which people must deal with contradictions, criticalities and problematic situations. The organizational culture change promoted within Comau’s context can be identified as an agile way of work , that requires: adaptability , maintaining a high level of flexibility and capability to adjust, modify and change a project during its life cycle, going beyond a predictive and waterfall top-down approach; visibility , allowing plural stakeholders to have a view of the multiple aspects involved and to acknowledge the complexity of what is at stake; value generation, since the beginning of the process spreading the concept of value to include not only economic but also eco-friendly, sustainable and ethic dimensions; risks facing, seeking for their reduction and management through a reconfiguration of the relationship connecting scope, time and cost. In a general market and organizational context characterized by a high level of uncertainty, relevant environmental chaos and complexity, an agile approach to work is preferred and recommended, to satisfy the expectations of customers ( Sletholt et al. , 2011 ).

The COVID-19 pandemic plays a relevant role in depicting such a scenario, in which practitioners and professional workers are coping with uncertain circumstances and facing contradictions in their daily organizational experience. At the same time, they are asked to make sense out of them, seeking new possibilities of action related to their object-oriented activity. In this perspective, the coronavirus situation can act as a litmus test and a situational organizer for both boosting the introduction and spreading the use of technological devices, as well as for soliciting the cultural change at different levels to cope with severe societal problems.

As shown by the Comau experience and vision, at stake is the need to place humans at the center both as technology recipients and guides toward technological progress. At the organizational level, this means giving back the responsibility of certain tools’ choices and their implementation to users. At the social level, this requires the awareness that humans create machines and that they are leading technological progress. Today this awareness is not a foregone conclusion, as the social anxiety about the impact of technologies on the social systems is due to the perception of technology as something external to humans that we can only suffer. To direct the technological progress toward the needs of the community, as the emergence of coronavirus is teaching us, a joint intervention of institutions, the academic world and the industrial world is necessary.

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Further reading

Frey , C.B. and Osborne , M.A. ( 2017 ), “ The future of employment: how susceptible are jobs to computerization ”, Technological Forecasting and Social Change , Vol. 114 , pp. 254 - 280 .

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The Fourth Industrial Revolution

What is the fourth industrial revolution.

The Fourth Industrial Revolution (4IR), also known as Industry 4.0, is a new era of development in which digital, physical and biological systems converge, fundamentally transforming industries, economies and societies.  

The term Fourth Industrial Revolution was coined by Klaus Schwab, Founder and Executive Chairman of the World Economic Forum (WEF). He introduced this concept in his book, The Fourth Industrial Revolution, published in 2016. In it, he discusses how emerging technologies like artificial intelligence (AI), the Internet of Things (IoT) and robotics have begun to merge with the physical, digital and biological worlds and, thus, have revolutionized economies, industries and societies in the process.   

 In this video, discover how the 4IR is transforming the world: 

• Transcript loading…

The 4IR’s alternate name, Industry 4.0, is usually referred to in the context of the manufacturing and industrial sectors. This term highlights the revolution's focus on the integration of digital technologies into the heart of industry to create smart factories that embody the convergence of the physical and digital worlds. 

This revolution is distinguished by its unprecedented speed, scope and impact on human life—it offers immense opportunities for progress but also poses significant challenges, including ethical considerations and the potential for increased inequality. Klaus Schwab argues that this era is more than just a technological upgrade—it’s an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. The 4IR compels us to rethink how we create, exchange and distribute value, with particular emphasis on the need for global cooperation and inclusive policies to harness its potential for the betterment of humanity. 

The 4IR expands upon the breakthroughs of the Third Industrial Revolution, also known as the digital revolution, that occurred from the 1950s through the early 2000s. During this time, innovations like computers, diverse electronic devices, the Internet and numerous other technological advances emerged. 

Fourth Industrial Revolution: Integration of Design and Technology 

The 4IR is marked by the integration of technologies like AI, IoT, robotics and VR, which demands a holistic design approach that considers not only the form and function but also the interconnectedness and intelligence of products and systems. 

The Apple Vision Pro epitomizes the convergence of design, technology, AI and VR—it’s a significant release of the Fourth Industrial Revolution. This device combines Apple's renowned design ethos with cutting-edge virtual reality capabilities to offer users immersive experiences that blur the line between the digital and physical worlds. The Vision Pro is powered by sophisticated AI to deliver personalized, intuitive interactions—it’s expected to set a new standard for how technology interfaces with human behavior.  

Watch Apple’s first announcement video for the Vision Pro: 

 As technology becomes more embedded in everyday life, design in the 4IR emphasizes user-centric solutions and personalized experiences, enabled by data analytics and machine learning. There's also a growing focus on sustainable and circular design principles driven by global challenges like climate change and resource scarcity. 

The complexity of 4IR technologies requires designers to work collaboratively across disciplines, integrating insights from engineering, biology, computer science and psychology. This interdisciplinary approach is crucial for innovation and for addressing the ethical, social and environmental implications of new technologies. 

The 4IR encourages designers to engage in speculative and critical design practices, exploring future scenarios and the societal impact of emerging technologies. This approach helps to envision potential futures and guide the development of technology in a responsible and human-centered direction. 

What Are the Key Technologies of the 4IR 

© Interaction Design Foundation, CC BY-SA 4.0

Artificial Intelligence (AI) and Machine Learning 

AI involves machines and programs capable of performing tasks that typically require human intelligence. Machine learning, a subset of AI, enables computers to learn from data and improve over time. These technologies are revolutionizing sectors by enhancing decision-making, automating tasks and creating new services and products. 

In this video, AI Product Designer Ioana Teleanu discusses AI’s impact on the world:  

 Learn more about machine learning in this video: 

Internet of Things (IoT) 

IoT refers to the network of physical objects embedded with sensors, software and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. This interconnectivity enables more efficient processes and improved data analytics, which impacts everything from home automation to industrial manufacturing.  

Smart lighting product, Philips Hue, uses IoT technology to offer a wide range of smart bulbs, lamps, and light fixtures that can be controlled via the Philips Hue app or through integration with other smart home systems. These lights can change color, brightness, and even sync with media content for an immersive experience. See how Philips uses IoT in their product expansion, Philips Hue Secure, in this video:   

Robotics technology involves the design, construction, operation and use of robots for various tasks. With advancements in AI and machine learning, robots are becoming increasingly sophisticated, capable of performing complex tasks autonomously or augmenting human capabilities in industries like manufacturing, healthcare and services. 

 In this video, Robotic company Boston Dynamics demonstrates how their robot Atlas can aid in construction:

Blockchain 

Blockchain is a decentralized ledger of all transactions across a network, which enables secure, transparent and tamper-proof record-keeping. While it underpins cryptocurrencies like Bitcoin, its applications extend to secure transactions, smart contracts and supply chain management. 

Organizations like IBM's Food Trust network uses blockchain to trace the production, processing, and distribution of food products to enhance safety and reduce waste.   

Quantum Computing 

Quantum computing represents a significant leap forward in computing power—it uses principles of quantum mechanics to process information at speeds unattainable by traditional computers. This technology has the potential to revolutionize fields such as cryptography, drug discovery and complex system simulation. 

Google's quantum AI lab is researching how quantum computing could accelerate machine learning tasks by processing complex data more efficiently than classical computers. Learn more in this video:    

3D Printing and Additive Manufacturing 

3D printing builds objects layer by layer from digital models. This offers unprecedented flexibility in manufacturing. It enables rapid prototyping, custom manufacturing and complex designs not possible with traditional methods which impacts industries from healthcare (with prosthetics and organ printing) to aerospace and automotive. 

 In this video by Mayo Clinic, 3D printing is used to create more hygienic and effective casts and splints for a patient with fractures and other injuries:  

Biotechnology and Genetic Engineering 

Advances in biotechnology and genetic engineering have enabled us to manipulate living organisms or their components to develop or make products, which improves healthcare, agriculture and environmental sustainability. Techniques like CRISPR-Cas9 gene editing have opened new possibilities for disease treatment and precision medicine. 

Learn more about gene editing in this video by TED-Ed:

Nanotechnology  

Nanotechnology manipulates matter at the atomic and molecular scale and promises significant advancements in materials science, medicine and electronics. Its applications range from more effective drug delivery systems to water treatment processes that remove contaminants at a molecular level. 

 In this video by Johns Hopkins Institute for NanoBioTechnology, learn how nanotechnology can be used to fight cancer:  

 Augmented Reality (AR) and Virtual Reality (VR) 

AR and VR technologies are changing the way we interact with digital environments. AR overlays digital information onto the physical world, while VR creates immersive digital environments. These technologies have applications in education, training, entertainment and beyond. 

 Learn more about VR, its history and its future in this video: 

Cyber-Physical Systems (CPS) 

CPS are integrations of computation, networking and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. This integration is foundational for smart grids, autonomous vehicle systems and smart factories. 

 In this video watch how a Tesla vehicle drives itself:   

These technologies are not only transformative in their own right, but are also interrelated. They often converge to create innovative solutions and opportunities across a variety of sectors and different levels of society and the economy. The potential of the 4IR lies in how these technologies are harnessed to drive forward human progress, address global challenges and reshape the world for the better. 

The Impact of the 4IR: Case Studies 

Environmental protection: iot for monitoring and conservation .

Rainforest Connection transforms recycled smartphones into solar-powered acoustic devices that monitor rainforest sounds. AI algorithms analyze these sounds to detect illegal logging and poaching in real time, enabling rapid response to protect wildlife and forests. This case study highlights how 4IR technologies can be creatively applied to combat environmental destruction and biodiversity loss. 

 Learn more about Rainforest Connection’s work in this video:  

Agro 4.0: More Efficient Farming 

The World Economic Forum’s (WEF) Centre for the Fourth Industrial Revolution (C4IR) introduced technology to small and medium farms in Colombia. The technology includes soil, water and climate sensors, as well as AI, cloud computing and drones. The project managed to reduce the farmer's costs by 30% and increase their yields by 20%.  

 Watch the C4IR video to learn more   

Healthcare: AI-Driven Diagnostics and Personalized Medicine 

Google's DeepMind developed an artificial intelligence system that can accurately detect over 50 types of eye diseases from 3D scans. Scientists from Google's DeepMind division, University College London (UCL) and Moorfields Eye Hospital developed software through deep learning techniques that can detect numerous prevalent eye conditions from 3D scans and subsequently recommend treatment options for the patient. This technology enables early diagnosis and treatment to potentially prevent vision loss in millions of people worldwide. Not only does it improve diagnostic accuracy and patient outcomes, but it can also reduce healthcare costs.  

© UCL, Moorfields, DeepMind, et al, Fair Use

What are the Impacts of the 4IR? 

The 4IR is not just a technological revolution; it's a catalyst for comprehensive change—how we live, work and relate to one another. Here are some of the major impacts and implications of the 4IR: 

Economic Transformation 

Productivity and efficiency : The integration of technologies like AI, robotics and IoT significantly boosts productivity and operational efficiencies across industries. In most cases, this leads to reduced costs, improved production rates and enhanced product quality. 

New business models and markets : The 4IR has enabled new, innovative business models (e.g., platform-based economies like Airbnb and sharing economies like Uber) and the creation of markets that didn't exist before, particularly in the digital and service sectors. 

Job displacement and creation : While automation and AI have displaced many traditional jobs, particularly in manufacturing and routine white-collar tasks, they also create new jobs that require advanced digital skills and competencies in technology development, data analysis and cybersecurity. 

Societal Changes 

Education and skill development : There's a growing need for education systems to adapt and an emphasis on STEM education, critical thinking, creativity and lifelong learning to prepare individuals for the jobs of the future. 

Inequality and digital divide : The benefits of the 4IR risk being unevenly distributed, which could exacerbate income inequality and widen the digital divide between those with access to new technologies and skills and those without. 

Enhanced connectivity and communication : The global proliferation of the internet and mobile devices has led to unprecedented levels of connectivity to enable new forms of social interaction, collaboration and information exchange. 

Technological Advancements 

Accelerated innovation : The rapid pace of technological advancement in fields like biotechnology, nanotechnology and quantum computing has already begun to revolutionize healthcare, energy and other industries.  

Cybersecurity challenges : As more devices and systems are connected, vulnerabilities to cyber-attacks increase. Data privacy and system security are increasingly critical challenges. 

Environmental Considerations 

Sustainable development : Technologies emerging from the 4IR offer promising solutions to environmental challenges, including more efficient resource use, renewable energy technologies and smarter, more sustainable cities. 

Climate change mitigation : Advances in technology are crucial for monitoring environmental changes, improving energy efficiency and developing new methods for carbon capture and storage to combat climate change. 

Ethical and Governance Issues 

Ethical considerations : The development and application of technologies like AI and genetic engineering raise profound ethical questions about privacy, consent and the nature of human identity. 

Regulation and governance : There is an increasing need for effective governance frameworks to ensure that the development and deployment of new technologies are aligned with societal values and ethical principles. Policymakers are challenged to keep pace with technological innovation while safeguarding public interests. 

The History of the World’s Industrial Revolutions 

The 4IR is built upon the foundation laid by the three previous industrial revolutions, each marked by a significant leap in technological capabilities that transformed societies and economies. It's important to understand these precursors as they provide essential context to grasp the scale and scope of the changes the 4IR represents. 

First Industrial Revolution: Late 18th to Early 19th Century 

The first Industrial Revolution’s start and end date are widely debated, but the general consensus is that it spanned from about 1760 to 1840. It was characterized by the transition from hand production methods to machines through the use of steam power and water power. The textile industry was among the first to be transformed, with the invention of the spinning jenny and the power loom. This era saw the rise of mechanized factories, which significantly increased production capabilities and led to urbanization as people moved to cities for work. 

A factory from the First Industrial Revolution. The machinery harnessed steam and water power.

© National Geographic, CC BY-SA 4.0

Second Industrial Revolution: Late 19th to Early 20th Century 

This period is roughly dated between 1870 and the beginning of World War I in 1914. The Second Industrial Revolution was marked by the introduction of electricity—this transformation led to more advanced manufacturing and production technologies. The development of the assembly line, notably used by Henry Ford in the mass production of automobiles, drastically increased efficiency and made goods more accessible to the masses. This period also saw significant advancements in chemical, electrical and steel production. 

The Ford Model T assembly line circa 1913-1914. Henry Ford was one of the first to use an assembly line for mass production. When a Model T left the assembly line at Ford's Highland Park plant to be shipped by rail, it was not fully assembled. In this photograph, workers temporarily place bodies onto a chassis. At the loading dock, bodies and wheels would be removed and packed separately to conserve freight car space. Full assembly took place at branch plants closer to the vehicles' final destination.

© The Henry Ford, CC BY-SA 4.0

Third Industrial Revolution: Mid-Late 20th Century  

Also known as the Digital Revolution, this era started around the 1950s-1970s. It’s defined by the move from analog electronic and mechanical devices to digital technologies. The invention of the personal computer, the internet and information and communications technology (ICT) transformed the way people live, work and communicate. It laid the groundwork for the globalized, interconnected world of today. The Third Industrial Revolution transitioned into the Fourth Industrial Revolution around the early 21st century, so there is no definitive end date for this period.  

Steve Jobs with the Apple II. It was released in 1977 and is an example of an early personal computer.

© Alamy, CC BY-SA 4.0

Fourth Industrial Revolution: 21st Century 

The 4IR builds on the digital revolution and is marked by a fusion of technologies that blur the lines between the physical, digital and biological. It’s characterized by breakthroughs in a range of areas including AI, robotics, the Internet of Things, genetic engineering, quantum computing and others. Unlike previous revolutions, the 4IR evolves at an exponential rate, transforming almost every industry and many aspects of human life. 

Each industrial revolution brought about drastic changes in economic structures, social systems and the global order. While the first three revolutions introduced and then expanded upon mechanization, electrification and digitization, respectively, the 4IR stands out for its potential to integrate cyber-physical systems and impact all disciplines, economies and industries on a global scale.  

How the Industrial Revolutions Have Impacted Design 

The industrial revolutions have profoundly influenced design. The technological, social and economic shifts of each era have shaped how, what and why humans design. Here's how each industrial revolution has impacted design: 

First Industrial Revolution 

Mass Production : The advent of steam-powered machinery enabled the mass production of goods, leading to product standardization. Design during this period focused on functionality and manufacturability, often at the expense of aesthetics and individuality. 

This British printed cotton textile is an example of the 1820 is an example of Regency design.

Second Industrial Revolution 

Industrial design : The introduction of assembly line manufacturing and advancements in materials and processes, such as steel production and electrical engineering, birthed the discipline of industrial design. Designers began to focus on the user experience, ergonomics and aesthetic appeal of products and thus recognized the value of design in marketing and brand differentiation. 

A Singer sewing machine circa 1880.

© Singer, Fair Use

The Singer sewing machine is a pivotal and recognizable invention from the 19th Century. Isaac Merritt Singer, an American inventor, patented the first practical sewing machine in 1851. Their machines were a combination of practical functionality with elaborate Victorian aesthetics. Its design not only made sewing more efficient and less labor-intensive but also turned the sewing machine into a desirable household item. In 1889, they released the first electric sewing machine. The Singer Company's innovations in mass production and global marketing strategies are classic examples of Second Industrial Revolution practices.  

An advertisement for the Singer 99k-13, the first electric sewing machine released in 1889.

Third Industrial Revolution 

Digital design : The Digital Revolution introduced computers and digital technology which revolutionized the way designers work. Computer-Aided Design (CAD) and other digital tools enabled more complex and precise designs to foster innovation in product development, architecture and graphic design. The rise of the internet also opened new avenues for digital and web design and emphasized user interface (UI) and user experience (UX) design. 

Milton Glaser's "I Love NY" logo was designed in 1977 for a New York State advertising campaign—it’s one of the most iconic works in graphic design. With its simple yet impactful composition, the American Typewriter font paired with a heart symbol replacing the word "love", Glaser's design captured the essence of New York City's resilience and appeal during a time of economic hardship and social unrest. This logo revitalized New York's image and showcased the power of graphic design in shaping public perception and fostering a sense of community and pride. Although the Digital Revolution was in its nascent stage, the impact of evolving technologies on design practices was becoming increasingly apparent.

© Milton Glaser, Fair Use

Learn More About the Fourth Industrial Revolution 

Read Klaus Schwab’s book The Fourth Industrial Revolution . 

Visit the World Economic Forum’s Centre for the Fourth Industrial Revolution .  

Read McKinsey and Company’s piece, What are Industry 4.0, the Fourth Industrial Revolution, and 4IR?  

Read about the World Economic Forum’s various 4IR projects . 

Check out National Geographic’s collection on the Industrial Revolution .  ​​​​

Questions about The Fourth Industrial Revolution

Emerging technologies such as AI and IoT are fundamentally transforming the design industry through the introduction of new capabilities for automation, personalization and connectivity. AI is being leveraged to automate routine design tasks, generate innovative design options and provide data-driven insights that can enhance efficiency and creativity. For example, Autodesk's Dreamcatcher is an AI-based generative design system that enables designers to input design goals along with parameters such as materials, manufacturing methods and cost constraints. The system then explores all the possible permutations of a solution and quickly generates design alternatives. IoT, on the other hand, integrates physical objects with sensors and software to allow designers to create interconnected products that can communicate with each other and with users in real-time. A notable example is the Philips Hue lighting system, which allows users to control light settings from their mobile devices, creating personalized environments.  

 Learn more about how AI is changing design and the world in this video with AI Product Designer, Ioana Teleanu:  

In the 4IR, essential skills for designers extend beyond traditional design competencies to include digital literacy, an understanding of emerging technologies and the ability to work with data. Proficiency in tools and platforms that leverage AI, IoT, VR/AR and 3D printing has become increasingly important. For instance, designers must be adept at using AI for user experience personalization and predictive analytics, as seen in platforms like Adobe Sensei, which helps automate and enhance creative tasks. Additionally, critical thinking, creativity and problem-solving remain foundational and enable designers to devise innovative solutions to complex problems. Collaboration skills are also vital, as the multidisciplinary nature of 4IR projects often requires working closely with engineers, data scientists and other specialists. The ability to continuously learn and adapt is crucial, given the rapid pace of technological change.  

 Learn more about essential skills for the 4IR in our courses AI for Designers , UX Design for Virtual Reality and UX Design for Augmented Reality .

The 4IR has significantly impacted UX and UI design practices by pushing the boundaries of customization, interactivity and user engagement. With the integration of technologies such as AI, IoT, VR and AR, designers are now able to create more personalized and immersive experiences. AI and machine learning offer the ability to analyze user data in real-time which enables the creation of interfaces that adapt to user behaviors and preferences. For example, Spotify uses machine learning to tailor music recommendations to individual tastes to enhance the user experience through personalization. 

 In addition, VR and AR technologies are redefining user interactions with digital products by offering immersive experiences that were previously not possible. AR apps like IKEA Place allow users to visualize furniture in their homes before making a purchase, merging digital and physical realities to improve decision-making and satisfaction. These advancements demand that UX/UI designers not only focus on traditional design principles but also on understanding and leveraging these emerging technologies to create seamless, intuitive and engaging user experiences. The emphasis on user-centered design has never been more critical as designers strive to ensure that technological advancements enhance rather than complicate the user experience. 

 Learn more about UX and UI Design for AR, VR and XR in our courses UX Design for Virtual Reality and UX Design for Augmented Reality , as well as our Master Classes How To Craft Immersive Experiences in XR and How to Innovate with XR .

Virtual and Augmented Reality (VR/AR) are transforming product design by enabling designers to create immersive and interactive prototypes which enhances the design process, user testing and user engagement. This capability is invaluable for industries such as automotive and architecture, where designers and engineers can virtually walk through a building or experience a car's interior before any physical prototype is built. For example, Ford uses VR to simulate car designs to allow for rapid iteration and testing of ergonomic and aesthetic features without the need for physical models. 

AR, on the other hand, overlays digital information onto the real world to enhance a user's perception of reality. This technology is particularly transformative in retail and interior design, as seen in. IKEA's AR app, IKEA Place. 

VR and AR technologies offer powerful tools for designers to not only improve the efficiency and effectiveness of the design process but also to create products and experiences that are more aligned with user needs and expectations. These technologies facilitate a more iterative design process, where feedback can be gathered and implemented quickly and lead to higher-quality and more user-friendly products. 

Learn more about UX Design for VR and AR in our courses UX Design for Virtual Reality and UX Design for Augmented Reality .

Klaus Schwab, Founder and Executive Chairman of the World Economic Forum (WEF) coined the term term the Fourth Industrial Revolution. He introduced this concept in his 2016 book of the same name. It remains the most influential book on the topic.   

Schwab, K. (2016). The Fourth Industrial Revolution. Portfolio. 

In the 4IR, data analytics plays a crucial role in design—it empowers designers with insights that drive more informed, user-centric decisions. Through the analysis of large datasets, designers can uncover patterns, trends and user behaviors that inform every stage of the design process, from conceptualization to final product development. This data-driven approach enables the creation of products and services that truly meet user needs and preferences. 

For example, in UX/UI design, data analytics can optimize user interfaces based on actual user interaction data and lead to more intuitive and effective designs. Companies like Netflix use data analytics to tailor content and recommendations to individual users, which enhances user experience. In product design, data analytics can inform feature development, usability improvements and even predict future trends, to ensure products remain relevant and competitive.  

Additionally, in the context of sustainable design, data analytics can identify areas where resources can be optimized or reduced, contributing to more environmentally friendly design solutions. Overall, data analytics bridges the gap between user expectations and design outcomes, making it an indispensable tool in the 4IR design toolkit. 

Learn more about data-driven design in our course Data-Driven Design: Quantitative Research for UX . 

Designers can leverage machine learning (ML) and AI in their work to enhance creativity, efficiency and user experience. One primary way is through the automation of routine tasks such as data analysis, which allows designers to focus more on the creative aspects of their projects. For example, Adobe Sensei, Adobe's AI and ML technology, automates complex processes like image editing and pattern recognition, to speed up the design workflow. 

Additionally, ML and AI can generate design alternatives and suggest improvements by learning from vast datasets of design elements and user interactions. This capability supports designers in exploring a wider range of options and making informed decisions based on predicted user preferences and behaviors. 

AI can also personalize user experiences in real-time by adapting interfaces, content and recommendations to individual user needs. Streaming services like Netflix and Spotify use AI to analyze viewing or listening habits, respectively, to deliver highly personalized content recommendations, to improve user satisfaction. 

Additionally, designers can use AI for more accurate user testing and feedback gathering. Tools powered by AI can simulate how users interact with designs to provide valuable insights without the need for extensive user testing sessions. 

Learn more about AI and ML, especially in the context of design, in our course AI for Designers . 

Watch the trailer here:  

In the Fourth Industrial Revolution, designers face several ethical considerations that stem from the increased use of emerging technologies like AI, IoT and big data analytics. Key ethical considerations include: 

Privacy and data protection : With the extensive collection and analysis of user data, designers must ensure they respect user privacy and comply with data protection laws. This involves designing systems that are secure by default and transparent about how user data is collected, used and stored. 

Bias and fairness : AI and machine learning algorithms can inadvertently perpetuate biases present in their training data, leading to unfair or discriminatory outcomes. Designers must strive to use diverse datasets and regularly audit algorithms to minimize bias. 

Accessibility and inclusiveness : The 4IR offers opportunities to make designs more accessible to a wider audience, including people with disabilities. Designers have a responsibility to ensure their products and services are inclusive, providing equal access and opportunities for everyone. 

Sustainability : With the growing concern over environmental issues, designers must consider the ecological impact of their designs. This includes choosing sustainable materials, designing for energy efficiency and considering the entire lifecycle of products to minimize waste. 

Accountability and transparency : As AI systems become more autonomous, designers must ensure that these systems are transparent in their decision-making processes and that there are mechanisms in place for accountability, especially in critical applications like healthcare or autonomous vehicles. 

User autonomy and manipulation : Designers need to be mindful of not creating manipulative designs that exploit user psychology for profit, such as dark patterns that trick users into making decisions against their interests. 

An example of ethical design in practice is the development of AI in healthcare, where designers and developers are working to ensure systems are transparent, explainable and free from bias to recognize the critical impact these systems have on patient care and outcomes. Ethical considerations in the 4IR are complex and evolving, requiring designers to stay informed and engaged with the latest developments in technology ethics. 

Learn more about the ethics and transparency in AI in the article AI Challenges and How You Can Overcome Them: How to Design for Trust .  

The role of human-centered design (HCD) is evolving significantly with the advent of the 4IR technologies, such as AI, IoT, VR/AR and big data analytics. HCD's core principle is to design with a deep focus on the needs, wants and limitations of end-users. That remains intact, but the scope and impact of this approach have expanded dramatically. 

In the 4IR, HCD is not just about products and services that are easy and intuitive to use; it's increasingly about how designers can leverage technology to make life better, work more productive and societies more inclusive. For example, AI and machine learning are being used to create more personalized experiences in everything from healthcare apps that provide tailored health advice, to educational platforms that adapt to the learning pace of individual students. 

In addition, HCD in the 4IR means designing for ethics and sustainability—to consider not just the immediate impact of a design on users, but also its long-term effects on society and the environment. This includes using IoT to create smart cities that enhance the quality of life, employing VR to train medical professionals without the need for physical resources and applying big data analytics to tackle complex social issues like poverty and climate change.  

Learn more about HCD in our Master Class Human-Centered Design for AI and our article Human-Centered Design: How to Focus on People When You Solve Complex Global Challenges . 

The Fourth Industrial Revolution has had a profound impact on sustainable and inclusive design—it’s offered new opportunities and challenges to create solutions that are environmentally friendly and accessible to all. The integration of technologies such as AI, IoT, VR/AR and big data analytics into the design process enables more informed decision-making, which leads to designs that can better address environmental concerns and social inequalities. 

In terms of sustainability, 4IR technologies allow for the optimization of resources and energy efficiency in product design and manufacturing processes. For example, AI can be used to analyze and predict patterns in energy consumption, which leads to the development of smarter, more energy-efficient buildings. Similarly, 3D printing technology enables the production of components with minimal waste and the use of sustainable materials further reduces the environmental footprint of manufactured goods. 

From an inclusivity perspective, 4IR technologies are breaking down barriers for people with disabilities and those in marginalized communities. For instance, AI-powered assistive devices can improve the quality of life for people with visual or auditory impairments, while AR and VR technologies offer new ways to experience content and services for those who may be physically unable to access them in traditional ways. 

Moreover, big data analytics play a crucial role in identifying and addressing gaps in accessibility and inclusivity and enable designers to create products and services that cater to a wider range of needs and preferences. This data-driven approach ensures that design decisions are based on real-world insights for more effective and impactful solutions. 

Learn more about sustainable design in our piece What is Sustainable Design? Take our course Design for Better World with Don Norman for an in-depth learning experience. 

Literature on The Fourth Industrial Revolution

Here’s the entire UX literature on The Fourth Industrial Revolution by the Interaction Design Foundation, collated in one place:

Learn more about The Fourth Industrial Revolution

Take a deep dive into The Fourth Industrial Revolution with our course Design for a Better World with Don Norman .

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Our world is full of complex socio-technical problems:

Unsustainable and wasteful practices that cause extreme climate changes such as floods and droughts.

Wars that worsen hunger and poverty .

Pandemics that disrupt entire economies and cripple healthcare .

Widespread misinformation that undermines education.

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Don Norman has constantly advocated the role of design. His book “The Design of Everyday Things” is a masterful introduction to the importance of design in everyday objects. Over the years, his conviction in the larger role of design and designers to solve complex socio-technical problems has only increased.

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In lesson 2, you'll learn about and explore multiple examples of sustainability and circular design in practice. In lesson 3, you'll dive into humanity-centered design and learn how to apply incremental modular design to large and complex socio-technical problems.

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The Fourth Industrial Revolution: Its Impact on Artificial Intelligence and Medicine in Developing Countries

• Perspective
• Published: 25 May 2024

Cite this article

• Thalia Arawi   ORCID: orcid.org/0000-0003-0443-5821 1 ,
• Joseph El Bachour   ORCID: orcid.org/0000-0002-9473-9935 1 &
• Tala El Khansa   ORCID: orcid.org/0000-0002-4145-9841 1  

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Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Artificial intelligence can be both a blessing and a curse, and potentially a double-edged sword if not carefully wielded. While it holds massive potential benefits to humans—particularly in healthcare by assisting in treatment of diseases, surgeries, record keeping, and easing the lives of both patients and doctors, its misuse has potential for harm through impact of biases, unemployment, breaches of privacy, and lack of accountability to mention a few. In this article, we discuss the fourth industrial revolution, through a focus on the core of this phenomenon, artificial intelligence. We outline what the fourth industrial revolution is, its basis around AI, and how this infiltrates human lives and society, akin to a transcendence. We focus on the potential dangers of AI and the ethical concerns it brings about particularly in developing countries in general and conflict zones in particular, and we offer potential solutions to such dangers. While we acknowledge the importance and potential of AI, we also call for cautious reservations before plunging straight into the exciting world of the future, one which we long have heard of only in science fiction movies.

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Arawi, T., El Bachour, J. & El Khansa, T. The Fourth Industrial Revolution: Its Impact on Artificial Intelligence and Medicine in Developing Countries. ABR (2024). https://doi.org/10.1007/s41649-024-00284-7

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The Fourth Industrial Revolution will be people powered

For many members of the world’s workforces, change can sometimes be seen as a threat, particularly when it comes to technology. This is often coupled with fears that automation will replace people. But a look beyond the headlines shows that the reverse is proving to be true , with Fourth Industrial Revolution (4IR) technologies   driving productivity and growth across manufacturing and production at brownfield and greenfield sites . These technologies are creating more and different jobs that are transforming manufacturing and helping to build fulfilling, rewarding, and sustainable careers. What’s more, with 4IR technologies in the hands of a workforce empowered with the skills needed to use them, an organization’s digital transformation journey can move from aspiration to reality.

In this special edition of the McKinsey Talks Operations podcast, host Daphne Luchtenberg brings you highlights from a panel discussion on the importance of building workforce capabilities and shifting mindsets for successful digital transformation. The discussion took place recently as part of Lighthouses Live, the flagship event of the Global Lighthouse Network—a World Economic Forum initiative in collaboration with McKinsey & Company.

The conversation was led by Francisco Betti, head of advanced manufacturing and value chains and member of the Executive Committee at the World Economic Forum. It also featured Revathi Advaithi, CEO of Flex; Robert Bodor, president and CEO of Protolabs; and David Goeckeler, CEO of Western Digital. The following is an edited version of their conversation.

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Daphne Luchtenberg: In this new world of work, the impact of technology means new skills and new roles are emerging as fast as other roles change.

David Goeckeler: You know, change can be opportunity for everybody. So I think we look at it through that lens. Change doesn’t have to be a threat; it’s just the opposite.

Daphne Luchtenberg: I’m Daphne Luchtenberg, one of your hosts for McKinsey Talks Operations , and that was David Goeckeler, CEO of Western Digital.

His comments were part of a conversation about the use of digital technologies in manufacturing and production, and how there is a need for training and development programs to teach workers the skills to use [these technologies].

So while there is a common perception that digitization and automation are a threat to the world’s workers, companies at the forefront of the technology frontier have actually created jobs—different, new roles that are much more high tech than the roles of the past.

And with the current labor mismatch being felt in many countries, the time is now to further engage workers for a digitally enabled future.

The Global Lighthouse Network

This focus is backed by growing research proving that workforce engagement is key. Over the last several years, research with the World Economic Forum, in collaboration with McKinsey, surveyed thousands of manufacturing sites on their way to digitizing operations and have identified about 90 leaders. These are the lighthouses—sites and supply chains chosen by an independent panel of experts for leadership in creating dramatic improvements with technology. Together they create the Global Lighthouse Network, committed to sharing what they’ve learned along the way. A common theme among these sites is their worker centricity—they are supporting the frontline workforce, upskilling, and making jobs easier and more interesting.

In this special edition of McKinsey Talks Operations , we’ll hear from the CEOs of a few of these leading companies about how they are engaging their people and putting technology in the hands of the workforce. The conversation originally took place during Lighthouses Live, a recent event of the Global Lighthouse Network. The discussion is led by Francisco Betti, at the World Economic Forum.

Let’s listen in.

Francisco Betti: I am delighted to be joined by an impressive group of leaders from our Global Lighthouse Network: Revathi Advaithi, chief executive officer of Flex; Robert Bodor, president and CEO of Protolabs; and David Goeckeler, chief executive officer of Western Digital.

Revathi, Robert, David—a very warm welcome, and thank you for joining us today. We have an exciting conversation ahead of us. We will discuss how you are shaping the future direction of your companies by leveraging Fourth Industrial Revolution technologies and empowering and engaging your people.

Revathi Advaithi: The most important thing is that we’re a company of people. We’re 165,000 people in 30 countries. And I’m a big believer that culture is at the forefront of everything we do. And great manufacturing comes because you have a great culture.

My belief is that the recognition of [the Flex factory in Althofen, Austria] as a lighthouse site is because they have a fantastic culture—a culture that’s focused on innovation, that is very ready to embrace change, is willing to learn from other companies across the world. So it’s such an amazing recognition for that particular site. And it really opens up the avenue for every Flex manufacturing site to really strive to be at the level that Althofen is and to be at the level of the other 90 manufacturing sites that are lighthouse-recognized.

So we are very, very excited about it. We think that this is the start of using the Fourth Industrial Revolution to really build on the capability of our sites, and just build a sustainable manufacturing legacy for Flex.

Francisco Betti: Western Digital has also joined the Global Lighthouse Network with two sites this year—one in Penang, Malaysia, and the other in Prachinburi, Thailand.

In your lighthouses, we have seen success driven by a combination of technology and people. Can you share how Western Digital has been keeping people at the center of its digital transformation journey to realize its full potential?

David Goeckeler: Keeping people at the center is actually pretty straightforward because people are the number-one priority in our operations. We work in a very dynamic market, and we know that our teams, and the skill of our teams, is really what’s going to define our success in the future. So keeping them at the center is critical. And it’s not just the operations team; it’s everybody in the company. We have over 60,000 employees—from the people in operations all the way to the executive team—and everybody is involved and behind this exciting effort. So keeping our people, reskilling our people, building that future-ready workforce, is what’s critical for us, but also for our employees.

Any time in life when you learn new skills, when you educate yourself, I think you have the opportunity to live a better life. It’s not just about our company being better and us being prepared for the future; it’s about all of our employees being ready for that future—keeping them at the center, having them highly engaged, all of the reskilling, getting them excited about what the future holds.

This isn’t some kind of executive mandate; it’s the employees leading it, pulling the company to it. Keeping them all deeply engaged keeps them directly at the center of what we’re doing. And, as I said, having our employees fully engaged, really building that future-ready workforce, is going to be what defines the success of Western Digital.

Francisco Betti: Thank you very much, David. It’s great to hear about the importance of culture and people from both you and Revathi.

Let me ask you a follow-up question. What advice you would give to those companies that are still stuck in pilot purgatory and are trying to scale digital transformations?

David Goeckeler: First of all, what we just talked about is workforce engagement. It’s got to be a pull, the workforce has to be fully engaged, you have to take the time to train and explain all the things about what success is going to mean for everybody. And you have to get that alignment from the shop floor all the way to the executive team on what going to a new model is going to deliver. And, as I said, not just for the business, but for all the individuals.

This is a new world. In manufacturing, there’s going to be a lot of fast and big data. Make sure you have a scalable industrial IoT stack that’s going to be able to handle that and be ready. David Goeckeler

Then I would point people to infrastructure readiness. This is a new world. In manufacturing, there’s going to be a lot of fast and big data. Make sure you have a scalable industrial IoT [Internet of Things] stack that’s going to be able to handle that and be ready.

So first make sure the workforce is engaged. Make sure the infrastructure is ready so that you don’t run into roadblocks. And then really prioritize. Pick use cases that are going to have a big impact. As the team says, “Think big, start small, and then scale fast.”

We’ve had a lot of success doing that—picking use cases that are going to have big business impacts. People see the value. You start to build momentum. And once you get some momentum going, it’s easier to keep it going and build faster and more of it. So, again, workforce engagement, infrastructure readiness, and then start with some prioritized use cases. Start small but think big. And then scale as fast as you can.

Francisco Betti: That is great advice, David. Thank you.

Revathi, let me come back to you now. Flex’s lighthouse in Austria was facing tough competition from lower-cost regions. However, your teams were able to leverage technology to build a more attractive product lineup. What are the key lessons your company learned from this? How does it inform your future strategy?

Revathi Advaithi: When you walk into our Althofen site, the first thing you notice is the “can do” culture. As the world went through labor arbitrage and manufacturing moving to more competitive regions of the world, Althofen has been a thriving site that has focused on using technology as a competitive advantage.

We have a site that is very well trained in terms of skilling. They’re able to skill and reskill, like David talked about, at an amazing pace with really good change. And the second is, tremendous resiliency. They’re able to bring up new products at a fast pace versus any other site that I’m aware of just because they have that spirit of innovation and the focus on technology.

Pretty much any complexity of product, they’re able to bring into their facility and scale up for a customer, and really respond to any of the market dynamics present. All of this has resulted in a site that’s having tremendous rigor—operational rigor—lots of agility, in terms of how they operate.

The results have been incredible for that site. They’ve had tremendous revenue growth while improving margins. But most importantly, they’ve made some sustainable change, which I really love. CO 2 emissions have improved significantly for that site. And we have driven reductions, in terms of our travel costs and those things in that site, just by use of technology—whether you’re thinking about simulation or any of those other technologies that have been used.

Francisco Betti: Thank you, Revathi. Amazing achievements.

Robert, this seems like the perfect opportunity to bring you in. Firstly, many congratulations for the recognition of your Plymouth site as a lighthouse—Protolabs’ first lighthouse in our global network.

As a medium-size enterprise, you embarked on an amazing journey to transition from providing prototypes to becoming an at-scale production supplier—and you did that by incrementally developing new digital capabilities.

What did you do to further accelerate your 4IR journey, considering your company was already a digital native?

Robert Bodor: As you alluded to, Protolabs was founded over two decades ago with a digital mindset from the start. We began as an injection-molding company looking to transform the traditional manufacturing process. Our mission was to automate traditional manufacturing in order to provide molded parts in days at a fraction of the price of traditional molders.

Over time, we extended this digitalization approach to other services, including CNC [computerized numerical control] machining, sheet metal fabrication, and 3-D printing. So, Revathi, you’re right, we love additive manufacturing at Protolabs.

As our name implies, we targeted engineers, who had needs for prototypes to begin with. But over time, we found that our customers were using us for production-part needs and that they valued us for our quality, our reliability, and our willingness to make parts on demand with no minimum-order quantities, so that they could virtualize their inventory and reduce their supply-chain risks, especially in times when demand was volatile.

So that realization was really key for us. And that launched the 4IR journey that you mentioned, Francisco, from being a prototype provider to, now, also a production provider. To do that, we had to extend our digital thread, which connects our online quoting platform to the shop floor and to the customer.

We already had end-to-end automation in place that allowed us to make a mold from scratch and shoot molded parts in one to 15 days. But now, we needed to extend that for these production applications. So we adopted 4IR technologies to expand that system. And it included things like processed automation, digital-part inspection and validation, and process control, which included implementing an industrial IoT stack that allows us to conduct real-time monitoring of our mold presses and associated equipment. And then close the loop in all of that.

All of this expanded the digital thread and the digital twin of key elements of our production processes so that we truly had this end-to-end connection from the online quote all the way through the production process and, ultimately, to the customer.

Lastly, we also implemented a scaled agile development framework, because software is at the core of our business and what we do. And this framework allowed several hundred software developers who are serving our injection-molding business to be able to be agile and coordinated at that scale and to respond to the needs of the plant and to the customers as they evolved.

Francisco Betti: Excellent. Thank you for sharing that, Robert. It sounds like an amazing journey. David, coming back to you now, and I’d like to focus once again on the importance of people.

Your lighthouses in Thailand and Malaysia have several thousand workers, and you’ve focused heavily on upskilling and reskilling. In fact, in Thailand, 60 percent of your workforce was reskilled to support and accelerate technology adoption. And that resulted in zero job losses, which is just fantastic.

How are you turning this approach of reskilling at scale into a competitive advantage for your company?

David Goeckeler: Our successes depended on our people. And let me give a little bit of background on what these people are building. Western Digital is a diversified storage company. An easy way to think about us is, 40 percent of the data that’s stored in the world is stored on a device that our team built.

That’s kind of an amazing stat: 40 percent of the data in the world that’s stored is stored on a device that these teams built. And the demand for that storage is increasing at a 35 percent yearly compounded annual growth rate. So there are plenty of things to do, and the technology allows us to build that.

And it’s our responsibility to equip and empower that team for our short-term and our long-term success. This is a very large imperative that we have a workforce that’s ready for the future that we’re building. We have thousands of engineers who are designing the products of the future that are going to enable the digital economy we all live in. Making sure we have a workforce that’s ready to build that technology is critically important to us.

So it’s really about making Western Digital the employer of choice in the regions that you saw. And that’s about that stronger workforce engagement—training them, letting people know that when you come to Western Digital, you’re not just going to do the job you have today, but you’re going to learn new skills.

We’re able to take our very experienced employees and our workforce that really knows how our business works and bring them into the future, and at the same time attract new people into the business. So I think it’s a win for everybody, and it’s been a great journey and a tremendous success.

Francisco Betti: Thank you, David. Robert, can I ask you what your thoughts are here?

Robert Bodor: I would agree with David’s comments. And furthermore, I would add that the manufacturing industry today, particularly the American manufacturing industry, is experiencing a severe labor shortage. And this has potential long-term implications.

A National Association of Manufacturers study indicated that over two million manufacturing jobs could go unfilled by 2030. As a digital manufacturer, we’ve worked to automate a great deal of our manufacturing process, which allows us to be more efficient with our workforce. And that’s one of the competitive advantages that’s coming to us from our 4IR initiatives.

However, our employees are absolutely critical to our success. So the challenge is real. And at Protolabs, we’re dedicated to creating what we hope are long-term career opportunities for our employees on the shop floor. And that requires considerable investment in creating learning opportunities that will help them grow.

We’ve put a really concerted focus on upskilling our employees to ensure that they’re able to grow in their careers and develop the skills that are vital in this Fourth Industrial Revolution. But for us, that includes things like in-house training and certification programs for key roles, like our mold technicians, for example.

Our online learning portal offers hundreds of courses that can help our employees to grow. [We provide] tuition reimbursement for continued learning opportunities at universities and trade schools. Further, we really work to incorporate technology on the job so that we can improve the employee experience on the manufacturing floor and support their on-the-job training through technology.

Ultimately, our goal is to ensure that our employees have the path to become experts in the modern best-practice methods that we’re using, such as scientific molding in the case of Plymouth, and also to grow other skills, like A3 problem solving, change management, leadership development.

Francisco Betti: Excellent, Robert. Thank you. Revathi, one final question to you. At Flex, we have seen your incredible efforts to reskill almost the entire IT team and your shop floor operators. They are all smart manufacturing experts by now.

It’s core for the survival of companies, and, more importantly, its core for our people strategy, because the best way to keep our employees, our colleagues, excited about what they do is to make sure that they are at the forefront of every technology they use. Revathi Advaithi

Revathi Advaithi: Francisco, just like Robert and David talked about this, I think it’s core for the survival of companies, and, more importantly, its core for our people strategy, because the best way to keep our employees, our colleagues, excited about what they do is to make sure that they are at the forefront of every technology they use.

I’ll give you an example. The facility here in Austin typically makes a lot of technology products, whether it is storing security products, things like that. But recently, we had to start moving a lot of medical products into Austin.

One reason for this is because it’s a fantastic location to have. But two is because we also have a great team there. But the team had to really change their entire mindset. They had to learn a fully automated, wholly sophisticated set of equipment and how to run it, and really pick up new skills that they didn’t have before, including FDA [US Food and Drug Administration] compliance for a lot of regulatory issues.

But we were able to train the team based on other sites, learn from them, and really change the competency of this site in the last couple of years. Althofen, the site that is recognized as a lighthouse today, has done that time and time again, many times over.

We have a system called Pulse that we deploy across the organization. Pulse, truly, is the heartbeat of the organization. Althofen was one of the first sites that deployed Pulse. They know in real time exactly where all the product is—what is coming in, what is leaving, how much inventory is in the system—so they can give real-time updates to the customer to provide them a seamless transition.

The idea of all those sites was “unless we learn first and we get to the table first, it is survival of the fittest and the best team wins,” right? So we are able to have sites that have the culture of “we want to be the best.” And what has been amazing about [the Global Lighthouse Network] is we get the ability to benchmark and learn from other sites, then bring it in, and then really reskill our workforce.

Francisco Betti: There are millions of facilities and companies around the world that we want to reach and engage in the unique learning opportunity the Global Lighthouse Network provides. Our network will continue to grow, and we invite you all to reach out to us to be able to experience the journey toward becoming a lighthouse.

Daphne Luchtenberg: That was a great discussion, and thank you again to our panelists and our colleagues at the World Economic Forum for an insightful event. Once again, organizations are selected to be part of the Global Lighthouse Network based on their leadership and willingness to share their insights. If you are inspired to begin your own Lighthouse Learning Journey, we invite you to learn more on McKinsey.com/GLN , or on the World Economic Forum website .

This program is just one in a series that considers the challenges that companies and economies are facing, as well as the opportunities that leaders can seize for competitive advantage. We will explore other important topics, such as how to connect boardroom strategy to the front lines, where and when to infuse operations with technology, and why empowering the workforce with skills and capabilities is key to success.

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