Balancing autonomy and control: how ChatGPT adoption shapes gig worker performance in the knowledge economy

Purpose This study investigates the role of personal innovativeness in shaping the intention to use chatGPT and its impact on the performance of knowledge-intensive gig workers in China. It further examines the mediating role of intention to use chatGPT and the moderating effect of perceived algorithmic control on enhancing gig worker performance. Design/methodology/approach Primary data were collected from 440 gig workers engaged in content creation, digital marketing, AI-assisted services and consulting recruited from multiple platforms. A structured online questionnaire using a five-point Likert scale was administered in two waves to reduce common method bias. Smart PLS 4.0 was employed to test the hypotheses through structural equation modeling. Findings Findings reveal that personal innovativeness positively influences both the intention to use chatGPT and gig worker performance. Similarly, intentions to use chatGPT has a positive impact on gig workers performance. The intention to use chatGPT mediates the relationship between personal innovativeness and performance, while perceived algorithmic control strengthens this relationship. Practical implications These insights offer practical guidance for platform managers and policymakers to enhance gig worker performance by fostering innovativeness, promoting AI adoption and designing algorithmic systems that balance guidance with autonomy. Originality/value This study contributes to the knowledge-intensive gig economy literature by integrating personal, technological and organizational factors to explain performance outcomes and demonstrates how AI adoption, moderated by algorithmic control can boost productivity in platform-based labor markets.