Call for papers – Special Issue – The Generative Workplace: The Lived Experience of Generative AI at Work
Special Issue – The Generative Workplace: The Lived Experience of Generative AI at Work
Personnel Psychology invites submissions for a special issue on “The Generative Workplace: The Lived Experience of Generative AI at Work.” Generative AI is arguably the first innovative technology to enter the workplace that can substantially produce, analyze, summarize, and provide guidance on the content of work itself, including the text, code, images, audio, and video that constitute significant components of knowledge work. This positions generative AI as impacting the substance of professional work: how people write, design, build, decide, persuade, mentor, evaluate, and relate to one another.
Given the unprecedented rate of growth in AI use, adoption has far outpaced cumulative empirical evidence. Amidst this technological change, our aim is to ensure that the human perspective is not lost – in fact, successfully integrating the human perspective becomes the central challenge, which highlights the need to take a sociotechnical systems perspective on AI implementation seriously.
The key organizing question for the special issue is: How does using generative AI change the experience of work, workplace relationships, identity, leadership, and organizational culture? We treat generative AI as an increasingly present part of the daily subjective experience of working life that impacts individuals, teams, and organizations.
We seek theory-grounded, practice-relevant, empirically rigorous work on the subjective and relational experience of using generative AI at work, and on the consequences of that experience for workers, teams, and organizations. The unifying lens is experiential and human-centered: not only whether generative AI changes output, but how it feels, what it changes about how people relate, and what new norms, experiences, identities, and tensions may emerge.
Submission window: 1 August – 27 August 2027
The Special Issue is guest edited by Louis Tay, Sarah Bankins, and Markus Langer. Their contact details can be found at the call for papers linked below, and they welcome interested colleagues to contact them.