Mapping the Human-AI Collaboration Trends in Design Research: A Systematic Review

This systematic review provides an overview of the academic discourse on human-AI (HAI) collaboration within the design discipline. The selected papers were analysed through action coding, encapsulating the papers’ approach—designing, evaluating, discussing, and structural coding, indicating the papers’ core topics— human creativity, training, specific tasks, collaborative environments, ethical concern, interaction, co-creation, communication, decision-making, trust, and team dynamics. The papers are analysed and visualised in a network based on their assigned codes, revealing their relationships to one another. This interpretative effort contributes to knowledge by developing a bottom-up coding approach to identify key discourse clusters within the rapidly evolving literature on HAI collaboration, defining and discussing such clusters, and recognising relevant trends in the debate. The review highlights a current emphasis on practically driven studies over critical and reflective ones, suggesting the need for more integrated approaches that combine both perspectives.