1.1 Introduction

There is an ongoing digital transformation with an increasing diffusion of technologies that are acting as a catalyst for business advancement. The first chapter discusses the importance of sustainable digital transformation at this point in time and explains why each case was chosen, the common threads and some key findings. Each case brings a different piece of the puzzle, but it also serves to test and verify our current understanding of digital transformation. There are common lessons across all cases, along with the specific lessons some cases offer for those specific sectors of the economy. The research presented here is practical, with directly applicable lessons for organizations, but it also raises broader questions about how digital transformation is sha** the workplace, our private lives and society in general. There are cases of sustainable digital transformation in finance, tourism, transport, entertainment and social innovation that inform this discussion.

The main theme of the research presented here is to address organizational challenges and pitfalls experienced during the implementation of, and experimentation with, digital transformation. The research here aims to reveal an eclectic mix of examples, experiences and best practices in the business sector, where the seeds of digital transformation are set. The research here aims to provide historical cases as well as taxonomies of digital transformation in the business sector, along with their impact on selected corporate entities. It includes cases and best practices from industry leaders in the technology and implementation of digital transformation. The interrelation among people, technology and organizational structures are significant themes of the research presented here. The use of new and emergent Artificial Intelligence (AI) tools to achieve digital transformation in businesses, as well as future trends in AI, is the dominant characteristic of this research. The target audience of this research is all the stakeholders engaged in this process such as managers, software developers and researchers.

The nine main themes identified here are as follows: (1) Digital transformation leaders will constantly innovate, while digital transformation laggards will have a stop-start approach. (2) There are no simple answers, or a single way to go forward, with digital transformation. (3) Each sector of the economy has its own opportunities, challenges and must find its own path forward. (4) Changes in one sector of the economy, such as the financial sector, will send a ripple of change across other sectors of the economy. (5) Change needs a shared vision, and digital transformation needs leaders to create the shared vision. (6) Digital transformation needs trust and cooperation on every level: Teams, organizations, governments and super-organizations like the EU. (7) People will still have a role: Staff, customers and other stakeholders are still important. (8) There is a dark side to digital transformation that may not have been fully revealed to us yet. (9) Digital transformation should happen hand in hand with sustainability and resilience.

The next section argues that sustainable digital transformation is an opportunity with far-reaching consequences. The third section builds on the cases presented here and finds nine common themes of successful digital transformation across the cases. Lastly the fourth section gives an overview of the fascinating chapters presented here.

1.2 The Importance of Sustainable Digital Transformation

Sustainable digital transformation is a term that is being used frequently in the last few years (Shi et al., 2022). It involves the union of technological change and innovative technologies. Digital transformation with Artificial Intelligence can offer scalability not seen before. It involves constant innovation, evolution and acceleration. It is true that technology is an enabler of digital transformation, but transformation often involves people, technology and new business models. How are these interlinked? Do they function individually or together to make digital transformation a success? Is one force more decisive than others, or are they equally important? With the increasing capabilities of AI and the speed of automated services that can be delivered, is human involvement still necessary? Will we keep human involvement out of nostalgia, so we have something to do, or will roles evolve so that the human involvement still adds value?

Leaders in large and small, public and private organizations appreciate the transformational impact of new technologies such as Artificial Intelligence, big data, cloud computing, Internet of Things (IoT), blockchain and 5G but are unclear on what their organization should look like in the future and how to get there (Pflaum et al., 2019; Zarifis et al., 2021). The environment they find themselves in, with almost daily steps towards, and away from, globalization, new local and international regulation, further adds to this uncertainty (Herbert et al., 2019). These leaders are therefore looking for successful cases of digital transformation, in a variety of contexts, to guide them (Alt et al., 2018; Bátiz-Lazo & Efthymiou, 2016; Zarifis & Cheng, 2023).

While the unstoppable march of technology and the global instability may seem like enough of a challenge for a leader to understand, these are by no means the only forces driving digital transformation. There are also some more subtle, but still influential, forces at play. The post-pandemic worker is not as willing to sacrifice their quality of life for the promise of career advancement and the status that comes with it (Gupta & Mukherjee, 2022). With this mindset, the promise of digital transformation delivering a more efficient machine may not be enough, and people want to know where they fit into this picture. This zeitgeist is reflected in the increased interest in sustainability in its many facets (Purvis et al., 2019).

These forces pushing and pulling digital transformation, but also holding it back, bring us to one overarching question: What is the destination of the digital transformation journey? While some companies automate their processes one by one, when the opportunity arises, as we see with AI chatbots (Zarifis et al., 2021), there should be a clear idea of where this journey will take an organization. Taking all this into account, the leader of digital transformation should act like a true leader, taking staff, customers and other stakeholders with them on this journey.

Despite the challenges of a complex, ill-defined problem, there are also reasons to be optimistic (Vial, 2019). What emerges strongly from the research findings presented here and other literature reviewed here is the willingness to work together and learn from each other (Thrassou et al., 2022a). Leaders in digital transformation must become experts of technology in their context but also be receptive of the solutions found in adjacent contexts or even further away. A leader of digital transformation must disassemble the technology, processes, business models and strategies involved and then put together their own collage of what they want to achieve and their own montage of the journey there.

1.3 Common Themes Across the Chapters

As was touched on already, there were some common themes and key findings that came out strongly in this research that will be discussed in more detail here. The common themes from the chapters are also areas for future research to further explore (Table 1.1).

Table 1.1 The major themes in digital transformation based on eight cases
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Major theme 1: Digital transformation leaders will constantly innovate, while digital transformation laggards will have a stop-start approach. Digital transformation leaders will rapidly innovate going through regular iterative evolutions of their technologies, moving through repeated cycles of agile developments metaphorically forming a ‘spiral’ or a ‘spring’. New innovations and in-house skills are built up in this process of constant innovation. Continuing with the metaphor this tightly coiled ‘spring’ will store ‘energy’ propelling the organization forward. Digital transformation laggards will have a stop-start approach copying certain solutions of the leaders but not kee** up. Metaphorically a far less tightly coiled ‘spring’, more like a line touching the leader’s tightly coiled ‘spring’ at some points and missing other points. Digital transformation followers will create less innovations and not build up in-house capabilities as much (Fig. 1.1).

Fig. 1.1
An illustration presents a series of arrows like a tightly coiled spring with three straight arrows passing through the coil without touching the curved arrows indicating the digital transformation leaders' innovation and followers.

The tightly coiled ‘spring’ of digital transformation leader’s innovation and the followers

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Major theme 2: There are no simple answers, or a single way to go forward, with digital transformation. If this were purely a case of technology adoption, then there would be some typical approaches such as selecting the best of breed for each application, or by adopting a tried and tested Enterprise Resource Planning system (ERP). The importance of each context limits the availability of generalizable solutions. The availability of data is vastly different for different organizations. Due to the far-reaching consequences of digital transformation, it comes up against legal and regulatory limitations more often, and these are very context specific (Slok-Wodkowska & Mazur, 2021).

Major theme 3: Each sector of the economy has its own opportunities, challenges and must find its own path forward. Following on from the previous point, while it is difficult to identify generalizable solutions, there are more specific approaches that show promise. We see here examples from using machine learning to manipulate video in real time, blockchain being utilized in a supply chain and how to build trust in Fintech. These solutions have often emerged after a variety of alternatives were explored. They are valuable lessons in digital transformation that can help a leader move forward with digitization and automation faster, more sustainably and with lower risk of failure.

Major theme 4: Changes in one sector of the economy, such as the financial sector, will send a ripple of change across other sectors of the economy. Digital transformation may be happening at different speeds, and change may not be happening in lockstep between sectors in the economy, but some changes in one place send ripples across business and society. For example, finance is a part of many other organizations’ value chain, and beyond that has responsibilities to the economy and the people where it is active. Changes brought by Fintech, such as greater accessibility to banking and loans, make it easier for small businesses, particularly in rural areas, to have access to credit and grow. The barriers to accessing finance and technology are being reduced in many cases. While it is asking too much from a leader to predict when and how a change somewhere else will impact them, they should be able to react quickly and should not be caught flat-footed.

Major theme 5: Change needs a shared vision, and digital transformation needs leaders to create the shared vision. Digital transformation requires changes to the organizational structure and culture of an organization. While machine learning may offer a solution for scalability and diversification, this also requires broader co-ordination to implement. The division between business and technology must be reduced, and a more innovative agile approach must be ingrained into people (Panetta, 2016; Vial, 2019). A transformational leader is needed that will support the development of a new shared vision based on values that resonate with people. In most cases, these shared values include customer focus, ease of use, sustainability and resilience. In practice this means running more operations of a business as projects and taking advantage of the ecosystem around the organization.

Major theme 6: Digital transformation needs trust and cooperation on every level: Teams, organizations, governments and super-organizations like the EU. There is evidence that organizations are appreciating the magnitude and far-reaching nature of digital transformation, and they are trying to reach some consensus in how to move forward. There are aspects of digital transformation that are opportunities to gain a competitive advantage, but there are also areas that need co-ordination and collaboration between competitors, regulators and other stakeholders. The collaboration will need trust so that there is openness between competitors on the challenges they face and even sharing of data, for example, for machine learning to be trained. The increasing role of technology not only requires more collaboration but also offers the means to do this by providing more immersive environments in virtual worlds, also known as the metaverse.

Major theme 7: People will still have a role: Staff, customers and other stakeholders are still important. This is not just about work, but many other aspects of our lives including digital transformation (Thrassou et al., 2022b). There are pitfalls to over-relying on technology and data. There is a long history of data being created and interpreted in a misleading way leading to tragic consequences (Hodson & Quaglia, 2009). The financial models that led to the 2008 economic crash often presented new investments as secure because the data on them did not go far back enough to include the previous busts in the almost inevitable boom-bust cycle. While the capabilities of machine learning are impressive, it does not escape the old adage of garbage in, garbage out. Despite the increased role of technology, it will not lead, and it will not dictate what will happen. Even in a scenario where the leaders of an organization are sufficiently enamoured with AI to let this happen, there will be pushback from the increasingly knowledgeable and actively engaged consumer.

Major theme 8: There is a dark side to digital transformation that may not have been fully revealed to us yet. The research presented here presents several effective implementations but also some failures that could be useful lessons. However, all the research here, while acknowledging the occasional error of humans engaged in this process, illustrates the value of being ‘in the loop’, influencing decisions and learning from them. Being fully engaged on a daily basis is necessary so that people with skills and judgement are there to deal with the negative implications of digital transformation that are here and those that will come later. The negative implications that resonate most currently are the ethical issues and personal information privacy concerns. An artificial agent’s automated reasoning may make judgements that are not acceptable by humans (Bonnemains et al., 2018). When we are looking at a simple case of cause and effect, this may be easy to resolve, but this becomes more challenging with interrelated processes that have indirect outcomes. For example, in the research we present here, particularly the research on Fintech and video augmentation, we see some indirect and unexpected consequences.

Most of us have heard the metaphors such as data being the new oil, the new gold and so on. What some people may not fully appreciate yet is how much personal information is being used and how invasive the insights can be. Most people are comfortable with data being collected on their purchases, but when the insight gained on them extends into their health and information on their beliefs that can be manipulated, this becomes harder to accept. The expansion of digital transformation and the data collected on staff and other stakeholders increases the power of those controlling the data, typically the employer, and reduces the power of the staff and others whose data was collected. There are two extremes to dealing with this. The first is to push digital transformation and ‘force’ staff to accept it. In a similar way to how an authoritarian leader would do. The second approach is to act with a more inclusive spirit and co-create the digital transformation.

Major theme 9: Digital transformation should happen hand in hand with sustainability and resilience. Digital transformation and sustainability are, rightly, two of the most researched topics in recent years. Both can be implemented in a small scale at the organizational level but require broader collaboration to harness the greatest benefits possible. AI and automated processes need to operate in a sustainable way (van Wynsberghe, 2021), as there are limited resources. Sustainable AI must not harm the environment and be fair to society (van Wynsberghe, 2021). Similarly, many approaches to achieving sustainability, such as the circular economy, benefit from AI and automation (Wilson et al., 2022). The social, economic and environment pillars of sustainability will benefit from the way AI removes the barriers of scalability.

1.4 Overview of the Chapters

Chapter 2

The second chapter ‘What Are We Automating? On the Need for Vision and Expertise When Deploying AI Systems’ by Alexander Rast, Vivek Singh, Steve Plunkett, Andrew Crean and Fabio Cuzzolin offers a fascinating case of a cutting-edge application of machine learning. This research illustrates capabilities of machine learning that few people know about. This research offers a glimpse into the development of advanced AI solutions, but it also gives some useful lessons on the process of deployment. The process of deploying the AI solution involves the interplay of the developers, the business purchasing it and their clients. Along with many new insights this research reinforces some very familiar and repeating themes in digital transformation such as the importance of data and the limitations that insufficient data sets on a system.

Chapter 3

Like the second chapter, the third chapter provides another case of applying new technologies to solve a business problem. Many of us have had problems with our baggage when travelling, so this is a chapter that resonates with many of us on a very personal level. The research is on ‘Blockchain in the Aviation Industry: A Decentralized Solution to the Transparency Issue in Baggage Handling’, and it is by Mads Jørgsholm Bierrings, Gerishanth Sivakumar and Nico Wunderlich. Airline travel is expanding drastically, and legacy systems are struggling to keep up. The existing legacy systems have proven over the years that they cannot be optimized beyond a certain point, and they have their inherent limitations. The attributes of blockchain and RFID technologies can improve many of the processes in an airport, particularly the baggage handling as we see in this case. With low-cost airlines having very low profit margins and low flexibility to resolve customer problems, having a more reliable system will be beneficial. With blockchain and RFID as the underlying technologies, transparency is enhanced, and the value of data extracted from tracking luggage can be unlocked.

Chapter 4

In the fourth chapter we move from the application of specific innovative technology to a taxonomy of business models. The chapter ‘The Five Emerging Business Models of Fintech for AI Adoption, Growth and Building Trust’ is by Alex Zarifis and Xusen Cheng. The five Fintech business models are (a) disaggregating and focusing on one part of the value chain, (b) utilizing AI in the current processes without changing the business model, (c) finance incumbent extending their model to utilize AI and access new customers and data, (d) a startup finance disruptor only getting involved in finance, and (e) a tech company adding finance to their existing portfolio of services. For all five Fintech models the way trust is built should be part of the business model. Trust is not always built at the same point in the value chain or by the same type of organization. The trust building should happen where the customers are attracted and onboarded. The five Fintech business models give an organization five proven routes to AI adoption and growth. The five distinct approached identified also make it easier for a company in finance to understand what their competitors are doing. Simlarly, regulators in this area can benefit from the clarity the taxonomy offers.

Chapter 5

The fifth chapter explores the improvements technology can bring to seaports and the cruise industry, complementing the chapter on airports nicely. The chapter ‘Digital Transformation and System Interoperability in EU Seaports: A Platform Facilitating Supply Chain in the Cruise Industry’ is by Leonidas Efthymiou, Paraskevi Dekoulou, Yianna Orphanidou and Eleftherios Sdoukopoulos. The analysis examines the implementation of the National Maritime Single Window (NMSW), the adoption of a European Maritime Single Window (EMSW) and how these systems support the development of a supply-chain platform in the cruise industry. The findings suggest that digital transformation through NMSWs and EMSW contributes to data transfer in real time. Also, the interoperability of systems creates a digital environment where other systems co-exist, facilitating connectivity between the public and private sectors. However, more formalized strategizing is needed, to leverage cooperation between public and private stakeholders in the ever-changing digitized environment.

Chapter 6

The sixth chapter looks at the application of a new technology with far-reaching consequences. ‘The Six Ways to Build Trust and Reduce Privacy Concern in a Central Bank Digital Currency (CBDC)’ is by Alex Zarifis and Xusen Cheng. A Central Bank Digital Currency (CBDC) offers many potential benefits for governments and citizens, such as faster transactions at a lower cost and richer information on consumers’ behaviour. It is important however that the consumer’s perspective on the adoption of CBDCs is not neglected. A CBDC needs consumers to trust and use it, to avoid either a complete failure or a partial failure, leading to CBDCs being part of two parallel systems. This research identifies the six ways to build trust in a CBDC so it can be successfully adopted: (1) Trust in the government and the central bank issuing a CBDC, (2) expressed guarantees for the user of a CBDC, (3) the positive reputation of existing CBDCs active elsewhere, (4) automation and reduced human involvement achieved by a CBDC technology, (5) trust building functionality of a CBDC, and (6) privacy features of the CBDC wallet app and back-end processes such as anonymity.

Chapter 7

The seventh chapter explores the sensitive issue of personal information privacy and puts forward some innovative and practical solutions, illustrating the important role that the public sector has in digital transformation. The chapter ‘Insight and Control over Personal Data: A View from Sweden’ is by Theodor Andersson. The research explores ways to increase citizen engagement and knowledge of the value and use of personal information as a way to offer better and more individualized services. There are some legal challenges that need to be investigated further so that they can be overcome, and an ecosystem can be implemented offering increased individual insight and control. The main focus of this research is on the potential conflict between an individual’s right to gain further insight and control and the prerequisites and incentives for authorities to realize such insight and control. This research can inform a workable and sustainable solution for all the stakeholders on this important issue.

Chapter 8

Several chapters have identified how important the context is to digital transformation, so it is useful to see in this chapter the context of the service sector in India being explored. The chapter ‘Digital Transformation in the Indian Service Sector: Benefits, Challenges and Future Implications’ is by Ambika Kulshrestha, Sandeep Kulshrestha, Leonidas Efthymiou and Despo Ktoridou. The chapter examines the impact of digital transformation in four areas of the organization, namely culture, processes, people and business model. The findings show that positives outweigh the negatives, hence it can be deduced that technology was as per the expectations of most managers. However, considering the impact on each individual ‘area’, it can be easily deciphered that digitalization had neither a good nor a bad impact on the organizations. Interestingly, those who experience a positive impact by digitization are mostly chief executives and senior managers, whereas those who experience a negative impact are managers in middle and junior positions. Such findings reveal that digitization is experienced differently by people in different roles.

Chapter 9

The social implications of digital transformation are in the periphery of several of the other chapters, so it is beneficial that in this chapter they take centre stage. The chapter ‘The Impact of Digital Transformation on the Sustainable Development of Social Innovation, Socio-ecological Resilience and Governance’ José G. Vargas-Hernández, M. C. Omar C. Vargas-González and Leonidas Efthymiou. This chapter examines how digital transformation influences Social Innovation, along with its impact on socio-ecological resilience and governance. The analysis departs from the assumption that Social Innovation has a strong dependence relationship with socio-ecological resilience and governance. However, confronted with the imperatives of an increasingly digital work, social systems are challenged to maintain coherence and simultaneously explore innovating and sustainable paths. Therefore, we have to look more closely at Social Innovation alongside digital transformation. It is concluded that digital transformation is itself a form of Social Innovation. This is because digitization facilitates a framework of enhanced communication, problem-solving and knowledge sharing. Within this framework, digital transformation becomes a driver of Social Innovation, while it enables greater interconnection with socio-ecological resilience and governance.