ECIS 2027

SIG AI Track 17 - Artificial Intelligence and the Future of Organizing

Link: https://ecis2027.uni.lu/track-17/

SIG AI Track Chairs: Laura Watkowski, Sarah Hönigsberg & Dan O'Leary

Track description

Artificial Intelligence (AI) has rapidly entered organizational 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 organizational evolution, alongside normative assumptions about progress, responsible adoption, and future readiness. However, the integration of AI into organizations 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 organizational 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 organizing 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 organizations make sense of, legitimize, 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 organizing, 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, legitimized, and made sense of in organizations? Which normative assumptions, technological imaginaries, and organizational priorities shape its adoption, design and use? How do organizations 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 organizations 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, organizational learning around AI, resistance and contestation, vendor and platform dependencies, value-laden system design, and the broader organizational 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, organizational 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 organizing.

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.