Using unique data from LinkedIn profiles, we measure the adoption of AI technologies by mutual fund managers. Compared to low-AI funds, high-AI funds generate superior returns and incur lower expenses. AI outperformance is particularly strong among discretionary funds, which rely on human judgment, as opposed to quantitative funds. The greater the AI adoption, the more pronounced the time-varying skill of fund managers across different market conditions. The stock-picking abilities of high-AI funds improve with the availability of big data, such as satellite imagery of parking lots. The local availability of AI skills is a key determinant of cross-sectional variation in mutual fund AI investment. Our findings are robust to using geographic variation in AI supply as an instrument for AI utilization by mutual funds.

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.