Relying on AI at work reduces self-efficacy, ownership, and meaning while active collaboration mitigates the effects.

Artificial intelligence (AI) promises major productivity gains, but it also raises fundamental questions about how technology can reshape people's relationship to their work. Historical debates over industrialization warned that technological change could undermine people's connection to work and sense of meaning. Similar concerns now surround AI, where the key issue may not be whether AI is used, but how it is used. Across a pre-registered experiment (N = 269) and a follow-up survey (N = 270), we examine how different modes of AI use affect the confidence individuals have in completing work without AI assistance (self-efficacy), their sense of ownership over task output, and the meaning they perceive in their work. Participants completed occupation-specific writing tasks under one of three conditions: no AI use, passive AI use (copying AI-generated content), or active collaboration (drafting first and then using AI to refin). We find that passive use undermined self-efficacy, psychological ownership, and work meaningfulness, with declines in efficacy and meaningfulness persisting even when participants returned to manual work. In contrast, collaborative AI use preserved psychological connection to the task, producing outcomes comparable to independent work. Although passive use initially boosted enjoyment and satisfaction, these benefits reversed once participants resumed manual work. A complementary real-world survey mirrored these patterns across tasks beyond writing. Together, these findings show that the psychological consequences of AI use hinge on how it is integrated into human workflows, underscoring that strategies promoting active, collaborative use may help capture AI's productivity benefits while preserving human workers' agency, competence, and connection to their work.