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Artificial intelligence and augmented reality are two key tools gaining importance in the digital era due to their wide range of applications in different fields and sectors. Industry 4.0 lays emphasis principally on the technology used to help the business remain competitive and sustainable. Sustainable development goals are another important objective of the UN which has laid responsibility for every business to support addressing the global challenges. Purpose: This chapter essentially aims to present the standpoint of artificial intelligence and augmented reality in meeting the sustainability perspective of organizations. Information about the study is gathered through secondary approaches, critically reviewing published literature, scientific reports, and statistical data accessible through business reports, and corporate websites. Further analyzed to present the perspectives of the authors in the study. Globally artificial intelligence market size is predicted to reach $190 billion by 2025, while the funding for startups doubled during the period 2011–2020 globally. The investment in artificial intelligence is going to reach $500 by 2024 resulting in substantial revenue returns. The augmented reality market size could reach $97 billion by 2028. Artificial intelligence today is increasingly used in many fields and is attracting multiple applications in many sectors such as manufacturing, retail, education, IT, and health care and has also contributed to sustainable development the same time by providing energy conservation options, optimization, and reduction of resources, minimizing wastage, offering timely assistance on maintenance schedules, practices which are enabling organizations to reach closer to sustainability and transformation.

The shift to the fourth industrial revolution presents new sustainable development challenges. The externalities of the second and third industrial revolutions were related to the degradation of the biosphere. It is suggested that the externalities of the fourth industrial revolution, underpinned by artificial intelligence, are extending the repertoire of externalities to include the degradation and manipulation of cognition and by extension the fabric of society. The implications for South Africa’s transformation within the fourth industrial revolution are highlighted. It is shown that digital nudging and choice architecture are tools that are capable of maximising profit while externalising social value through the algorithmic manipulation of our decision-making processes. The case for an alternative explanatory framework is presented because the limitations of the prevailing conception of physical reality appear unable to adequately resolve these super-wicked problems. Constructor theory is introduced as an alternative explanatory framework, and the constructor-theoretic conception is suggested as an ontological framework that will provide better explanations. Some principles of the theory are introduced.

A wave of technological change in the first decades of the twenty-first century is prefiguring a fundamental restructuring of society. Key among the driving forces behind such change are powerful technologies with the potential to exert major transformations on a range of human activities and, crucially, to do so without direct human intervention. The technologies collectively referred to as Artificial Intelligence, or AI represent a productive lens through which to investigate two interrelated transformations: the emergence of self-driving cars and the coming shifts in education. This is in particular because AI’s versatility has led it to be directly applied (and increasingly valued) both in new automated driving technologies, and in the development of new forms of instruction. From the educational perspective, this means that the same technologies that are transforming workforce conditions are also reshaping – directly and indirectly – the approaches, objectives, and experiences of students and educational institutions. This chapter lays out how these twin transformations are likely to play out in the case of the automotive industry and the educational pathways of two occupations closely associated with it: automotive engineers and repair technicians. Two key arguments underpin this examination. First, educational programs for these two occupations, (and beyond) should be broadened to develop versatility and adaptability through tools and perspectives that allow people to move vertically within organizations and laterally across industries in the face of rapid technological change. Second, these educational programs must explicitly tackle AI and the coming technological revolution from a variety of dimensions that connect technical skills acquisition with the context on how these technologies are incorporated in society, how they are governed, and what are the various responses to them. This will allow students and professionals to navigate a rapidly changing labor landscape better while endowing them with the vocabulary to actively participate in the debates that shape its construction.

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

Smart scenarios related to industries or cities, characterized by intensive technology transfer and use of innovative and disruptive technologies, have been in the spotlight either on academic or organizational discussions, especially those with a technocentric focus. Among these technologies, artificial intelligence (AI) emerges as the most challenging one due to its complexity. Therefore, this chapter aims to address AI, in particular the future of the labor market, exploring the challenges regarding the skills required in the context of AI technology, addressing its uses, challenges, and benefits. In order to achieve this goal, a systematic review was conducted on the extant literature using the methodology Methodi Ordinatio. The results show that the current literature is gradually changing from a more critical and negative view of AI to a more optimistic one, with more positive approaches and expectations regarding its benefits. As practical implications, the findings can be used as a guide for governments to develop strategies aiming to deal with upcoming challenges, especially regarding future jobs and employability.

This chapter explores conflict in digital transformation as a leadership challenge. The authors maintain that conflicts cannot be left to HR managers; rather, they must be anticipated, handled adeptly and made a leadership priority. Although conflict resolution is a well-researched area, this is not the case for authentic leadership in digital transformation. Thus, the field is ripe for empirical research. Pitman and Reilly call for research on conflict in digital transformation, the role of leadership in averting and resolving conflicts and whether these roles change understanding of authentic leadership. The impact of AI warranting a revision of orthodox authentic leadership theory represents a further domain of potential research.

Digital transformation has made enormous changes in the banking domain, where FinTech is the salient driving force inside it. Especially in the banking industry, Artificial Intelligence (AI) and Blockchain technology act as the most innovative technologies. Similarly, Chatbots in commercial banking and Robo-advisors in investment banking has shifted banks into the entire virtual environment. In this context, the main objectives of this chapter are: to determine the current application of AI and blockchain in the banking industry, to identify the challenges faced by banks in adapting AI and blockchain technology, and to provide new insights on future banking in the industry 5.0 in this digital era. This chapter discusses the application of two robotic platforms widely used in banking, chatbots, and Robo-advisors. Chatbots are more like frontline employees of banks who are commonly engaged in customer relationship management, sales, and marketing. In contrast, Robo-advisors are a relatively advanced AI tool involved in investment and portfolio management. Blockchain will accelerate digital transformation where a decentralized digital ledger system is used for banking transactions. However, this is entirely the opposite of conventional centralized digital banking, and the adoption of these technologies is still in its infancy. Employment, performance, security, privacy and trust, cost, ethical and regulatory challenges are the most common challenges. To avoid the challenges, banks should concern with strategies like collaboration with robots, increasing the platforms’ performance, etc. Finally, the chapter provides insights on banking at industry 5.0. In the future, banking customers can experience completely virtual and customer-oriented banking services. In this regard, the fusion of all technologies and collaborative human effort is essential.

There is a close relationship between labour markets and technology. Technological development enhances labour productivity and creates new jobs in some industries requiring to be different skills while it destroys jobs in ones requiring to be low-skilled. Today, it is experiencing a deep digital transformation. It may be evaluated for Industry 4.0 to cause technological unemployment due to changes in the structure of employment and to bring about new structural problems in labour market. In addition, it is expected for technological progress such as automation and robotic in the production process to negatively influence employment of low-skilled workers. Industry 4.0 has generated a new production model, in which robotic technologies are effectively used in the production process. So-called new technology-based production process has started to change production, working relationship and daily life. Discussions about the effects of the developments in technology on the labour market and unemployment are separated two groups. While there exist optimist views indicating that such development in technology will result in more productivity, pessimists believe that the use of robots, artificial intelligence, smart systems and algorithms in business life will eventually bring problems such as mass unemployment, mass poverty and social disruption. In this study, the authors aim to analyse the potential effects of Industry 4.0 on labour market in Turkey and European countries. From the findings of the study, the authors concluded that Turkey have a higher risk at automation than European countries.

The concept of Industry 5.0 is not just one more revolution but calls for a tectonic shift in digitization and operationalizing technology with connected value chain across sectors. It is human centric that promotes talents, diversity and empowerment coupled with resilience leading to agile and adaptable technologies with prime focus on sustainability. The COVID-19 pandemic has given impetus to digital transformation and accelerated the focus on other challenges of present time and with extended importance on people, planet and societal concepts. This study shall attempt to examine the nature of association between revolution of Industry 5.0 with perspectives to digital innovation and its implications toward bringing sustainable business model. The main objective of this chapter shall be to uncover interrelated questions in terms of sustainability perspectives of industries in framing business models. This study shall serve as a primer to significance of digital transformation with relevance to businesses that can lead to efficient use of scarce resources and optimal feasible solutions to the business models, given the institutional and organizational frameworks. Further, an attempt shall also be made to underpin the key facets of effects of Industry 5.0 on the knowledge economy. It shall delve into how digital innovations can yield benefits to industry in terms of competitiveness and sustainability with focus on Society 5.0 that attempts to balance economic development with the resolution of societal and environmental problems. It is not restricted to the manufacturing sector but addresses larger social challenges based on the integration of physical and virtual spaces.