Using LinkedIn profile data, we measure AI adoption by mutual fund advisers and show that high-AI funds outperform low-AI funds. This outperformance is concentrated among discretionary funds and among funds managed by more experienced managers, consistent with AI complementing human judgment rather than replacing it. Higher AI adoption is associated with stronger time-varying managerial skill---improved stock picking in normal times and superior market timing during periods of elevated risk. The stock-picking ability of high-AI funds further improves with access to large, unstructured data, such as satellite imagery. Finally, we show that local AI labor supply predicts cross-sectional variation in AI adoption, and our results are robust to an instrumental-variable strategy based on geographic variation in AI skill availability.

This paper examines AI adoption in asset management and its investment implications. We document that AI-driven investing is concentrated among hedge funds, particularly those employing macro strategies. AI funds exhibit greater alpha comovement and are launched by investment advisers facing stronger performance incentives. These funds significantly outperformed non-AI hedge funds on a risk-adjusted basis, but their outperformance declined over time and disappeared after 2018, consistent with decreasing returns to scale. Nevertheless, AI funds continued to outperform sibling funds managed by the same advisers. Our findings highlight both the alpha-generating potential and the limitations of AI as a source of investment performance.