When AI becomes a colleague: persona–organization fit and relational sensemaking in public organizations

Purpose This study aims to investigate how employees interpret generative artificial intelligence (Gen AI) during early adoption in public organizations. While existing research focuses on strategic frameworks, this study explores how relational sensemaking shapes Gen AI’s evaluation and integration in organizational life. Design/methodology/approach The research draws on qualitative data from interviews with 23 respondents across eight Norwegian municipalities. Using an abductive design, the author examined how employees narrate Gen AI’s role in their organizations, applying reflexive thematic analysis to derive theoretical insights. Findings Employees personify Gen AI through organizational roles. These personas guide evaluation across value congruence, accountability congruence, role scope and discretion and competence development. The author introduce persona–organization fit (POF) as a relational evaluative mechanism. Adoption occurs through dual onboarding and internal mobility (the “promotion” of Gen AI into trusted roles). Practical implications Relational framing provides managers with a governance tool by clarifying Gen AI’s role, boundaries and oversight structures for responsible adoption. The POF framework helps public sector managers align technological experimentation with accountability, risk management and competence-building strategies. Originality/value This study introduces POF as a theoretical lens advancing fit theory into the sociotechnical domain, showing how employees apply evaluative logics for human roles to technologies framed as organizational personas. POF complements and challenges technology adoption research by highlighting relational and normative evaluations through which employees position Gen AI within organizations. It extends sensemaking research by theorizing evaluative mechanisms shaping Gen AI’s organizational embedding.