Information Systems (IS) research is well-positioned but under-equipped to study technological futures at a time when claims about artificial intelligence (AI) are reshaping investment, policy, and public discourse. This perspective advances three arguments. First, IS scholarship should engage more systematically with digital futures, drawing on approaches for reasoning under uncertainty, such as Bayesian methods and established Futures Studies techniques, to distinguish prediction, projection, possibility, and hype. Second, technology hype is itself a legitimate object of IS research, and widely used frameworks such as the Gartner Hype Cycle appear limited in their ability to inform practice. Third, AI serves as a critical test case, combining heavy supply-side investment with unproven demand-side impact and unresolved questions of value and consequence. We propose four analytically distinct lenses for studying AI, namely, capability, adoption, value, and consequence, and identify two underexamined blind spots: bad actors deploying AI at scale and structural over-dependence on imperfect AI. We invite contributions to the Journal of Information Technology that examine how claims about technological futures are produced, circulated, institutionalized, resisted, and realized.

This paper argues that artificial intelligence exposes the shortcomings of traditional regulatory paradigms, challenging Easterbrook’s ‘Law of the Horse’ view that general legal principles suffice. AI’s opacity, autonomy, and systemic risks demand risk-informed, technology-specific governance. We identify the pacing problem, where innovation outstrips regulatory capacity, and propose a tripartite framework distinguishing functional, structural, and relational risks. Comparative analysis of EU, US, UK, and Chinese approaches highlights divergent logics of precaution, market oversight, hybrid flexibility, and state control. Effective governance requires embedding risk into policy design through adaptive, proportionate, and harmonised mechanisms, balancing innovation with accountability. The paper underscores the urgency of global coordination and calls for interdisciplinary IS research to inform anticipatory, participatory, and ethically grounded regulation.

“Digital futures” as a research field that examines diverse, long-term future(s) scenarios influenced by digital technologies has been proposed in information systems. Here, based on the emerging literature on digital futures, we define what this term means, delineate it from related concepts such as digital transformation, articulate why the information systems field should take note and consider the study of digital futures, and provide an overview of approaches.

Few industries have been as buffeted by change over the past 25 years as utilities. Industry restructuring, globalisation, deregulation, and digital technologies have up-ended a traditionally comfortable, almost leisurely operating model: regulated monopoly, vertically integrated supply, predictable demand, long service lifecycles, and highly commoditised products.

Our purpose in writing this book is to provide a realistic and reliable guide to planning and deploying successfully the digital technologies that will improve the performance of businesses. Selecting the technology turns out to be the (relatively) easy part. Putting it to work and gaining full value from it is anything but.

Today’s organisations are facing a digital catch-22. On the one hand, digital transformation is difficult and costly, and short-term investment may be needed elsewhere to where it’s really hurting. On the other hand, today’s organisations cannot afford not to become tomorrow’s digital businessesDigital business

This book provides a real-world journey map of automation, from RPA through to intelligent automation, with a focus on practical strategy

It can start with a problem … a challenge … an opportunity … an idea … or just curiosity. Whatever the impulse that sparks the imagination, it springs from the human instinct to invent, to challenge, to solve, to create something new.

In his hugely entertaining best-seller, 'Flash Boys', Michael Lewis tells the story of Dan Spivey, a stockbroker-turned-entrepreneur who built a straight-line fiber optic link between Chicago and New York City that allowed brokers to gain a few milliseconds advantage over their competitors in executing financial trades (roughly a tenth of the time it takes you to blink your eye).

Between 2021 and 2023 the general recognition was that telecom operators must marry operational efficiencyEfficiency and reduced capital expenditure with improved customer experiences, higher revenues, and greater business and operational resilience. Into 2023 we saw many operators using IA (Intelligent AutomationIntelligent Automation (IA)) technology to create new customer experiences and automate back-office processes. Others were deploying IA to better utilise 4G and 5G networks, or selling IA as a service to their enterprise customers. A recent development was telcosTelco (telecommunications company) using IA in conjunction with open application programming interfaces (APIs) and an open digital architecture. This allows them to evolve from being telcosTelco (telecommunications company) to techcos. The evolution to new revenues, including the monetisation of 5G, needs long-term software-defined, virtualised networks, cloud-based IT operations and open digital architectures. Another important part of these long-term moves, also helping to underpin today’s business is IA deployment.

In the previous chapter, we highlighted how financial services companies are applying imagination and combinatory innovation by shrinking the time lag between request and fulfilment, creating a ‘triple win’—for customers, employees, and shareholders.

In this chapter, we answer the key question: "What explains the superior outcomes automation leaders are getting against several market trends?" Our research shows that the single most important factor in achieving superior outcomes—one that shapes and informs all RPA-related activities—is the adoption of a strategic approachStrategic approach to the introduction and management of RPA within the enterprise.

To bring home the relevance of the KCP change framework and the complexity of the process, let’s examine an actual case of a company rewiring for digital transformation. By 2023 DBS Bank Singapore had long been globally recognised as an exemplar of how to achieve digital transformation.

During 2023, financial institutions were looking to boost by at least ten percent their investment in a variety of digital services, including mobile banking and asset management applications and online trading.

In our IT and business research over a 40-year timeframe, a distinct evolutionary pattern has emerged in technology adoption, impact and value. From Office Automation in the 1980s, through IT OutsourcingIT Outsourcing (and later BPO) in the 1990s and early 2000s, to the Internet and Cloud Computing and more recently RPA and Intelligent Automation, this pattern is self-evident and self-reinforcing: new technology is always initially valued and deployed as a vehicle for cost reduction.

In previous chapters we’ve looked at organisations that are applying imagination and combinatory innovation to gain velocity and to master scale challenges in their operations. In this chapter, we delve into the challenges presented by rising levels of complexityComplexity, and explore how leading organisations are using imagination and connected-RPA to align their operations more effectively with their business environments and customer needs.

Research at Knowledge Capital Partners has looked at the strategic use of intelligent automation/AI. We studied in particular automation leaders in five major sectors—banking, insurance, telecommunications, healthcare and utilities, and these sectors are covered in later chapters.