Generative AI is being rapidly integrated into workplace systems and HR processes, fundamentally reshaping how work is performed and productivity should be understood. The collaboration between humans and AI systems in task completion creates new challenges for measuring and attributing productivity outcomes, as traditional assumptions about performance metrics and human effort become outdated in AI-augmented contexts.
This special issue seeks research that reconsiders how productivity is conceptualized, measured, and compared when work involves human-AI collaboration. The call invites studies examining the distinction between AI adoption and actual use, the distribution of performance effects across different worker groups, implications for career development and employability, and the organizational and HR factors that influence AI-augmented productivity. Methodological contributions exploring innovative approaches to studying these phenomena are also welcomed.