The Generative Workplace: The Lived Experience of Generative AI at Work

Éditeurs invités

• Louis Tay, Purdue University
• Sarah Bankins, Macquarie University
• Markus Langer, University of Freiburg

Synthèse

This special issue examines how generative AI is reshaping the subjective experience of work across individuals, teams, and organizations. Rather than focusing on technical capabilities, it centers on what it feels like to work with AI systems like ChatGPT and Claude—how these tools influence engagement, relationships, identity, and organizational norms as adoption rapidly increases among knowledge workers worldwide.

The issue seeks empirically rigorous, theory-grounded research that closely observes generative AI in actual workplace settings. Priority is given to field research within organizations, implementation studies tracking deployment experiences, longitudinal designs, and rigorous qualitative research. Vignette studies, cross-sectional surveys of convenience samples, and conceptual papers without data are out of scope.

Submissions should articulate theoretical mechanisms for how generative AI changes work experiences, provide evidence credible for practitioners, and explicitly discuss practical impact for employees, managers, HR leaders, and policymakers.

Thèmes proposés

• Experience of work: Cognitive offloading and changes in effort, flow, and engagement; experiences of autonomy, competence, and ownership over AI-generated or AI-assisted output; changes to the meaning of work; skill development versus skill atrophy; work intensification versus work-life balance; changing nature of expertise; calibration of trust and over- or under-reliance; professional identity as roles shift
• Workplace relationships: Generative AI as a team member and its impact on social and working dynamics; emerging disclosure norms; trust, attribution, and competence judgments when AI is involved; migration of help-seeking and sensemaking from colleagues to AI tools; effects on collaboration, collegiality, reciprocity, informal mentorship, and organizational cohesion
• Training and development: Use and experience of AI as a trainer, coach, and mentor; development and declines in knowledge, skills, and abilities with AI use; lasting effects of AI-based training; comparisons of human trainers versus AI trainers; design of AI-based training and transfer to job performance
• Leadership: Leaders' use of generative AI for communication and the authenticity dilemma of machine-mediated empathy, vision, and feedback; leader decision processes with AI input; generative AI systems operating autonomously or in hybrid arrangements; what it feels like to be managed by generative AI
• Organizational culture: Emergent norms of acceptable generative AI use; psychological safety around disclosing versus concealing use; experience of monitoring and surveillance of workers' AI use or non-use; equity and felt divide between users and non-users; implications for inclusive workplaces