AI-driven investing – how is it performing?

The problem

Artificial intelligence (AI) has emerged as a promising tool in asset management because it can process large datasets, identify complex patterns, and adapt to changing market conditions. Despite the growing use of AI-driven investing (since the early 2010s), and strong interest from both fund managers and investors, there is limited evidence on where and how it is used in asset management, what its impacts are on markets, and whether it truly delivers better performance.

The research

To understand its role and effectiveness, researchers conducted a comprehensive analysis of AI-driven investing in the U.S. asset management industry by combining multiple data sources – from regulatory filings to job postings indicating AI-related hiring. Results show that while AI-driven investing has grown steadily, it remains niche, concentrated mainly among hedge funds. As for performance, AI funds significantly outperformed non-AI funds in earlier years, but this declined over time. Importantly, AI funds aren’t losing their advantage because they’re all copying the same strategy. Their performance, when adjusted for risk, tends to differ more from both other AI funds and similar traditional funds, suggesting they use a wider range of approaches rather than all following the same signals.

The impact

The findings provide nuanced insights for investors, fund managers and policymakers. They help explain when AI‑driven investing can improve investment performance and when advantages fade, supporting more informed investment decisions, and provide a clearer picture as to how AI is actually affecting the market – which challenges concerns that it is causing everyone to invest in the same way, supporting stronger policy and regulatory decisions.

Department: Finance 
Area: AI, finance