Artificial intelligence and the future of organising
Track 17
Track chairs
Laura Watkowski
University of Bayreuth
Sarah Hönigsberg
ICN Business School
Daniel O’Leary
University of Southern California
Track description
Artificial Intelligence (AI) has rapidly entered organisational contexts, often accompanied by promises of efficiency, innovation, competitiveness, and enhanced decision-making. These promises are frequently embedded in deterministic narratives that portray AI as an inevitable step in organisational evolution, alongside normative assumptions about progress, responsible adoption, and future readiness. However, the integration of AI into organisations is neither neutral nor straightforward. Rather, it unfolds through complex sociotechnical processes in which meanings are constructed, practices are negotiated, and arrangements are continuously reconfigured.
This track invites research that examines AI as an organisational and sociotechnical phenomenon, with attention to how AI is interpreted, justified, structured, and enacted in practice. While the track is open to research on AI-enabled organising more broadly, we are particularly interested in contributions that examine generative AI as a salient and rapidly diffusing form of AI that intensifies questions of agency, expertise, accountability, knowledge work, and sociotechnical change. More broadly, we are interested in how organisations make sense of, legitimise, and govern AI-enabled systems, as well as how AI reshapes work,
collaboration, expertise, and decision-making.
Beyond formal governance structures, the track encourages contributions that explore broader dynamics of organising, including tensions between human and machine agency, autonomy and control, experimentation and oversight, and technological promises and their practical consequences. Further, we invite particular attention to the deterministic narratives, normative assumptions, and tensions that accompany the adoption, use, and design of AI.
The track is guided by several core questions: How is AI framed, legitimised, and made sense of in organisations? Which normative assumptions, technological imaginaries, and organisational priorities shape its adoption, design and use? How do organisations govern AI-enabled work, and how are autonomy, accountability, and control reconfigured in practice? How does AI reshape collaboration, coordination, expertise, professional roles, and routines? How do organisations learn, experiment, and build capabilities around AI? What new boundaries between human and machine agency emerge? How do AI-enabled systems affect shared mental models, attention allocation, and collective sensemaking? And how can methodological and design approaches help us study and shape AI in organizational contexts?
Relevant topics include, but are not limited to, governance and control of AI, human–AI collaboration, AI-supported decision-making, changing forms of knowledge work, organisational learning around AI, resistance and contestation, vendor and platform dependencies, value-laden system design, and the broader organisational implications of AI adoption, use, and design. We welcome contributions from all research paradigms and methodological traditions, including qualitative, quantitative, mixed-method, experimental, and design-oriented research, reflecting the multidimensional nature of the phenomenon.
This track builds on recent ECIS and AIS conversations on intelligent digital futures (ECIS 2025) and the need to critically reimagine digital technologies for business and society (ECIS 2026). It aligns closely with the ECIS 2027 conference theme, “Bridging Digital Borders,” by examining how AI reconfigures boundaries between human and machine agency, organisational practices and platform infrastructures, and local contexts and global technological ecosystems. By exploring how such borders are constructed, negotiated, and contested, the track directly engages with the core concerns of the conference. We expect the topic to attract strong interest because it is timely while remaining distinctive in its focus on the deterministic and normative dimensions of AI-enabled organising
Topics of interest
- Governance, autonomy, accountability, and control mechanisms in AI-enabled work.
- Human–AI collaboration and evolving forms of coordination, particularly in generative and agentic AI settings.
- Boundaries of human and machine agency in organizational contexts.
- Transformation of knowledge work, expertise, and professional roles through AI, including generative AI-supported work practices.
- Organizing with AI around expertise, roles, and routines.
- Organizational learning, experimentation, and capability-building around AI and generative AI.
- Effects of integrating AI into enterprise systems, platforms, and digital infrastructures.
- Cognitive, behavioral, and social effects of organizational AI use.
- Sensemaking, framing, and legitimization of AI adoption and use.
- Value-laden design and the inscription of organizational priorities into AI systems.
- Responsible, ethical, and trustworthy AI and generative AI in practice.
- Technological imaginaries, deterministic narratives, and normative assumptions in AI and generative AI discourse.
- Methodological and design approaches for studying and shaping AI in organizations.
Associate editors
Philipp Spitzer
Karlsruhe Institute of Technology, Germany
Grant Oosterwyk
University of Cape Town, South Africa
Erwin Fielt
Queensland University of Technology, Australia
Rosemary Francisco
Universidade do Vale do Rio dos Sinos, Brazil
Jonathan Gomez
University of Southern California, USA
Bowen Lou
University of Southern California, USA
Arion Cheong
Stevens Institute of Technology, USA
Pauline Weritz
University of Twente, Netherlands
Ilias Pappas
University of Agder, Norway
Antino Kim
Indiana University, USA
Alan Dennis
Indiana University, USA
Guido Geerts
University of Delaware, USA
Mahei Li
University of Kassel, Germany
Mariam Jacobs-Basadien
University of Cape Town, South Africa
Hendrik Wache
ICN Business School, France
Pitso Tsibolane
University of Cape Town, South Africa
