The implications of artificial intelligence (AI) for work are significant and diverse, yet our understanding of its drivers remains siloed. This is partly due to a fragmented understanding of the AI phenomenon, its examination across diverse disciplines, and the contingent nature of its effects. We aim to help address these issues via two objectives. First, we explore the landscape of research by systematically reviewing how organizational science subdisciplines studying AI conceptualize, characterize, and investigate AI at work and then evaluate how this scholarship clarifies and contextualizes the phenomenon. By examining indicators of these dimensions, we identify distinct clusters of research that represent what we label as "application-orientation" and "generalized-orientation" categories. Comparatively, application-orientation research was the most likely to either define AI’s capabilities concretely or to situate their assessments within a specific function or industry, was less likely to characterize AI as a radically or wholly new and disruptive technology, less likely to contain claims regarding widespread technological unemployment resulting from AI, and less likely to focus on the negative (compared to the positive) outcomes of AI use for workers. Comparatively, generalized-orientation research was less likely to reference AI’s concrete capabilities or situate their analyses in a specific industry context, tended to be less empirical, and was more likely to position AI as radically disruptive or to focus on negative worker outcomes. Second, we seek to add to this research landscape by proposing an illustrative, interdisciplinary multilevel framework that suggests pathways toward balanced, multilevel assessments of the phenomenon.

While Artificial Intelligence (AI) promises to transform business models and enable novel service propositions, it also ushers in intricate managerial challenges. To comprehend AI’s disruption as well as harness its potential, we conducted a developmental review of 92 scholarly works centred on financial auditing, the chosen professional service domain. Drawing on the corpus of literature, we applied the Technology Affordance and Constraints Theory (TACT) to dissect the opportunities and challenges that AI introduces to professional services. Our analysis led to conceptualising AI’s affordances and constraints for individual practitioners, firms, and professional associations within the auditing domain. Subsequently, we compared these with the affordances and constraints of typical non-AI, classic IT tools in the same domain, highlighting the disruptive essence of AI. Our findings further revealed the reciprocal and tensional relationship between AI affordances and constraints, where actualising AI affordance at the firm level may impose constraints on individual practitioners. Based on our findings, we argue for integrating AI into decision-making by practitioners, propose a dynamic view of task automation and augmentation for firms, and urge an AI-calibrated knowledge system for professional associations. This study contributes to both theory and practice, laying the foundation for a more nuanced discourse on the strategic significance of harnessing AI in professional services.

IT alignment research has remained limited primarily to intra-organisational alignment, leaving much to learn about the value-creation potential of its largely neglected inter-organisational counterpart. This study addresses this gap by investigating the role of IT-business operational alignment in inter-organisational relationships (IOR). Drawing on IT-based value-co creation and IT alignment literature, we propose that IOR IT-business operational alignment is an immediate source for co-creating business value and can be established through a capability-building process. Using a sample of 241 regional network collaborations in Germany, we find that IOR IT-business operational alignment directly affects relationship performance. Moreover, we find that three IOR IT capabilities – IT infrastructure integration, information exchange capability, and IT-enabled coordination – enable the development of IOR IT-business operational alignment. This study contributes to IS research on value co-creation by integrating the concept of IT-business alignment into a nomological network with well-established IOR IT capabilities. We provide theoretical explanations and empirical evidence that IT infrastructure integration, information exchange capability, and IT-enabled coordination indirectly affect relationship performance over an operational alignment process. For practice, we highlight the importance of monitoring IT-business operational alignment in IOR and provide recommendations on how to expand existing alignment efforts.