Unintended consequences in Information Systems (IS) research are typically examined only after they have surfaced in practice, often treated as isolated instances rather than being systematically identified and understood. This reactive stance constrains our ability to anticipate risks, recognize emerging opportunities, and build cumulative insights across studies. To assess the current state of IS research on unintended consequences, we conducted a scoping review of literature in the Association for Information Systems' Senior Scholars' Basket of Journals. Our review highlights significant gaps in how unintended consequences are defined, theorized, and systematically compared. To address these gaps, we propose three foundational considerations: (1) conceptual clarity, to refine definitions and delineate boundaries; (2) relational configurations, to analyze the interplay between actors, technologies, and contexts; and (3) temporal configurations, to capture the evolving nature of consequences over time. Building on these dimensions, we introduce a set of guiding questions designed to provide shared analytical vocabulary rather than a prescriptive framework. These questions enable researchers to more systematically identify, categorize, and compare unintended consequences across contexts, thereby fostering theoretical precision, facilitating cross-contextual learning, and supporting a more anticipatory and comprehensive understanding of the phenomenon.

Digital platforms are increasingly integrating Generative AI (GenAI) tools as a boundary resource to enhance the quantity and quality of content with the ultimate goal of improving platform viability. As GenAI tools hold unique characteristics compared to traditional boundary resources, platform owners need to adapt their governance mechanisms accordingly. To understand how platform governance evolves over time in response to this novel boundary resource, we draw on the distributed tuning framework and build on insights from an in-depth qualitative study of a digital content platform in the educational sector. We find that the platform owner deployed different logics of GenAI integration over time that were enacted through specific governance mechanisms. The shift in logics and respective governance mechanisms was triggered by a dialectic process of resistance and accommodation between platform actors. In this process, the GenAI-enabled boundary resource not only changed over time but also served as a means for the power dynamics between platform owner and complementors to be reshaped. Our study contributes to both the platform governance literature as well as recent debates around GenAI.

Generative artificial intelligence (GenAI) is rapidly becoming a viable tool to enhance productivity and act as a catalyst for innovation across various sectors. Its ability to perform tasks that have traditionally required human judgment and creativity is transforming knowledge and creative work. Yet it also raises concerns and implications that could reshape the very landscape of knowledge and creative work. In this editorial, we undertake an in-depth examination of both the opportunities and challenges presented by GenAI for future IS research.

Work is increasingly being organised via online platforms outside guiding organisational structures. Instead of having colleagues at work, crowd workers connect in online communities. We investigate how crowd workers build professional holding environments in online communities to compensate for the lack of organisational structures and we consider how they craft their crowd work activities to enhance their work experience and reduce its long‐term precarity. Following a qualitative research design, this paper uses 675 forum interactions collected across six online communities. Based on our findings, we propose the concept of professional holding environments and provide a model for building such holding environments and job crafting in online communities. We thereby expand previous research on holding environments comprised of family members and friends by revealing the impact of professional online communities and their role in professionalisation and crafting supportive social structures in online crowd work.

Advancing digital collaboration and fostering effective communication among a widespread workforce continues to be a perpetual challenge for companies. Organizations are progressively turning to Enterprise Social Media (ESM) because they promise new avenues for collaborative working. However, most ESMs fail to reach a wider adoption by the workforce, owing to an underutilization by the employees. To enhance the understanding of the underutilization phenomenon, we use affordance actualization theory as our theoretical lens to critically study the challenges employees face in their attempt to actualize respective ESM affordances. By analyzing comments from 992 frequent, infrequent, and discontinued ESM users from a large multinational company, we uncover four major challenges. By enhancing our understanding of ESM affordances and by incorporating the full spectrum from problem identification to solution, we provide practical advice for digital leaders and meaningful theoretical implications for the IS community.

Artists make vital contributions to our society and lay the foundations for billion-dollar industries. However, these artists consistently struggle to acquire sufficient funding for their projects and their livelihood. New technology-supported possibilities for funding artists and their projects have emerged in recent years. Initial Coin Offering (ICO) is a novel form of reward-based tokenized crowdfunding. Although ICOs are promising as a way to fund artistic projects, they lack widespread adoption in the creative and cultural industry (CCI). Based on 35 qualitative in-depth interviews, we identify four barriers that hinder the funding of artistic projects through ICOs: legal shortcomings, investment restrictions, lack of consumer interest, and intermediaries’ resistance. Our research contributes to cultural finance and funding literature by disclosing barriers that impede a promising form of financing artistic projects. Further, we outline possible solutions to overcome them. We also contribute to the research about ICOs by showing that rather than reducing investment risks, these offerings merely shift them.

Blockchain gives rise to many new applications and use cases and has already markedly changed several industries, such as financial services, energy and utilities, or healthcare.Although blockchain could potentially be used disruptively for end-user applications as well, utilizing it remains poor.It appears that the unconvincing design of many end-user blockchain applications leads to insufficient user engagement.To investigate the influence of design aspects on users' engagement of blockchain end-user applications, we developed a blockchain application for the creative industries based on the principles of persuasive design.Hereby, we aim to contribute to research in the blockchain context on how end-user applications need to be designed to increase user engagement.By using a design science research process, we can ultimately provide a total of seven recommendations for developing persuasive blockchain applications for end-users.

Technological advances in the field of artificial intelligence (AI) are heralding a new era of analytics and data-driven decision-making. Organisations increasingly rely on people analytics to optimise human resource management practices in areas such as recruitment, performance evaluation, personnel development, health and retention management. Recent progress in the field of AI and ever-increasing volumes of digital data have raised expectations and contributed to a very positive image of people analytics. However, transferring and applying the efficiency-driven logic of analytics to manage humans carries numerous risks, challenges, and ethical implications. Based on a theorising review our paper analyses perils that can emerge from the use of people analytics. By disclosing the underlying assumptions of people analytics and offering a perspective on current and future technological advancements, we identify six perils and discuss their implications for organisations and employees. Then, we illustrate how these perils may aggravate with increasing analytical power of people analytics, and we suggest directions for future research. Our theorising review contributes to information system research at the intersection of analytics, artificial intelligence, and human-algorithmic management.

Artificial intelligence (AI) systems in the workplace increasingly substitute for employees' tasks, responsibilities, and decision-making. Consequently, employees must relinquish core activities of their work processes without the ability to interact with the AI system (e.g., to influence decision-making processes or adapt or overrule decision-making outcomes). To deepen our understanding of how substitutive decision-making AI systems affect employees' professional role identity and how employees adapt their identity in response to the system, we conducted an in-depth case study of a company in the area of loan consulting. We qualitatively analyzed more than 60 interviews with employees and managers. Our research contributes to the literature on IS and identity by disclosing mechanisms through which employees strengthen and protect their professional role identity despite being unable to directly interact with the AI system. Further, we highlight the boundary conditions for introducing an AI system and contribute to the body of empirical research on the potential downsides of AI.

Alongside the rapid development of artificial intelligence (AI), calls for responsible conduct have increasingly been put forward, particularly addressing the private sector as the primary owner of AI technologies. This demand for ethical conduct has given rise to the relatively new field of AI ethics, about which little is known in theory, and even less is known in practice. Recent studies on AI ethics have focused on organizations’ recent trend of issuing AI ethics guidelines; yet, in the corporate context, whether this principled approach actually contributes to ethical employee behavior, has been debated. Therefore, this study intends to identify measures and mechanisms which corporations operating across different industry sectors in Germany use to encourage employees in the implementation of ethical AI practices. Based on nine semi-structured expert interviews, besides AI ethics guidelines, we identify four more categories of applied implementation measures, namely, employee involvement, organizational anchoring, practical support, and hedging processes. Our study provides important insight into the under-researched field of applied AI ethics. Its findings provide a framework of implementation measures for corporate AI ethics, which is a significant starting point for both future research and companies that intend to encourage applied AI ethics among their employees.

AI systems are increasingly substituting human decision making. Based on an in-depth case study, we describe how one such AI system fulfilled the intentions of senior management for introducing it. However, we also identify the unintended consequences (positive and negative) of AI-based decision making for both employees and the organization. Based on this case study, we provide recommendations for introducing decision-making AI systems in a way that fully exploits the potential of these systems and manages the unintended consequences.(1,2)