ABSTRACT
This study examines how artificial intelligence (AI) reshapes gender dynamics in workplace negotiations. Adopting a technofeminist lens, we conceptualize gender–technology relations as mutually shaping and fluid. Using a convergent mixed-methods design, participants negotiated job offers with an AI chatbot recruiter. Qualitative transcript analysis identified gendered communication patterns, which were complemented by quantitative measures of negotiation outcomes and pre- and post-survey results. Findings reveal a paradox: AI-mediated negotiations muted traditional gender gaps—women and men achieved comparable outcomes—yet masculine-coded communication styles were associated with higher scores than feminine-coded communication styles. Participants also anthropomorphized the AI, projecting gendered identities that shaped satisfaction and outcomes. We introduce the concept of recursive human-AI gender learning to explain how humans and algorithms iteratively train one another, reproducing gendered communication norms within seemingly neutral systems. The study contributes to feminist AI scholarship by illuminating how AI both disrupts and reproduces gendered power relations in organizational life.