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As artificial intelligence rapidly evolves from novelty to infrastructure, a groundbreaking research study by Professor Zheng Sun and Assistant Professor Jinfei Sheng at the UC Irvine Paul Merage School of Business is exploring a pivotal question: Are generative AI tools widely adopted by hedge funds? What implications might such adoption have for their performance and the broader financial market?

Their working paper, Generative AI and Asset Management (co-authored with Professor Baozhong Yang from Georgia State University and Alan Zhang from Iowa State University), offers one of the earliest systematic analyses of how this new class of AI tools may reshape competitive dynamics within the finance industry.

Moving Beyond the Hype: What Makes This AI Wave Different?

Generative AI stands apart from past forms of financial automation. Unlike traditional predictive models, which are narrowly optimized and rely on structured historical data, generative AI can interpret narrative, sentiment, language, and context across earnings calls, geopolitical news, and regulatory developments and generate new, actionable insights.

“Generative AI doesn’t just forecast,” says Professor Sheng. “It constructs new interpretations of the world in real time. That creative reasoning ability, across messy, unstructured information, is what separates it from past forms of financial AI.”

The research explores whether such capability is beginning to show up in the actual performance data of hedge funds — and whether access to generative AI could benefit some hedge funds dramatically more than others.

What the Research Finds

Using a novel measure from hedge fund holdings, the research team documents a wide adoption of GenAI tools among hedge funds: more than 60% of hedge funds use GenAI tools for their investment decisions. This evidence is further supported by a unique new survey conducted in April 2025, which shows that about 70% hedge funds said they use GenAI tools for their investment decisions.

The study also examines whether this wave of AI levels the playing field or widens the gap.

“If the weaker firms move too slowly, the gap may widen faster than at any time in the last 30 years,” says Sun. “Generative AI has the potential to supercharge existing advantages, not automatically eliminate them.”

Whether AI democratizes access or accelerates competitive divergence may depend less on tool availability and more on a fund’s resources (e.g., capital and human). In particular, their AI talent. Hedge funds that hired AI talent before ChatGPT was launched tend to outperform in this race. This suggests a potential complementary relationship between GenAI and humans.

Implications for the Future of Finance

While the study is still evolving, Professors Sheng and Sun point to several early strategic signals for asset managers:

• Generative AI accelerates interpretation, not just prediction. It can analyze forward-looking narratives, not just past price movements.
• The winning edge will come from human-AI collaboration, not automation alone, especially where interpretation and adaptability matter more than speed.
• First movers with strategic discipline may unlock compounding advantage, far faster and more defensibly than in previous technology cycles.

This is not a hypothetical. It is an early look at how investment advantage itself may be redefined.

A UC Irvine Perspective

This research highlights UC Irvine’s leadership in examining how emerging AI technologies reshape the dynamics of the finance industry, not in theory, but in live economic systems.

Rather than asking whether AI can participate in finance, Professors Sheng and Sun are asking a far more urgent question: Who will control it, and who will be left behind?

Their work offers a critical early signal to asset managers, institutional investors, and policymakers about the strategic transformation already underway, and what it will take to stay ahead in the next era of financial intelligence.