How AI is affecting every job in hedge funds

Hedge funds aren't quite as vocal about their AI usage as banks, but rest assured (or be afraid) that use of the technology is widespread in the hedge fund industry. For some roles, the technology adds new dimensions and possibilities for career progression. For others it's a serious threat to their livelihoods. This is how AI is being used across each major role in a hedge fund.

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How AI is affecting portfolio manager jobs in hedge funds

Becoming a successful portfolio manager is the end-goal of many people who work in hedge funds. As the people closest to the money, they have the most to gain from AI and the most to lose.

Hedge funds have spent the last few years developing AI tools which make data analysis significantly faster and more robust. In March, OpenAI revealed that 95% of investment teams at Balyasny were using the fund's proprietary AI platform, which includes a deep research tool designed to replicate the work of a senior investment analyst in a fraction of the time. These tools conduct deep research on complex documents to gauge their potential impact on your investment portfolio. Much of this is done agentically; the fund's merger arbitrage team has AI agents proactively search for filings from companies involved in an M&A deal to continuously re-evaluate the fund's positions.

Citadel rolled out its own AI tool for equities traders last year. Then-CTO Umesh Subramanian said in December that the tool is used to highlight risk and will generate reading lists for traders based on their portfolio. Ken Griffin said in May that complex research which would take finance PhDs weeks to complete can now be done by AI agents in a matter of days. This places increased pressure on portfolio managers to translate all these insights into actual profit.

Knowing how to use these systems will therefore be an increasingly important part of portfolio management jobs. Man Group analyzed its own agentic tools in February and found that the quality of outputs depends on how a trader "build[s] and calibrat[es] the agentic system" as well as "how researchers frame questions and interpret results." Man Group advocates for "appropriate scepticism to avoid spurious findings."

How AI is affecting analyst jobs in hedge funds

Many of the top portfolio managers started their careers as investment analysts working underneath an established PM, analyzing documents and performing complex analysis to aid their decision making. The issue is that these duties, as we just described, can now be done much more efficiently with AI. An Anthropic report in March found that investment analyst roles were in the top 10 most exposed roles across any industry in principle... so where does that leave the analysts? 

Ex-Citadel and D.E. Shaw portfolio manager Brett Caughran said in May that it's increasingly common for hedge fund PMs to use AI in place of hiring a junior. Doug Garber, another Citadel alum who claims to have been ranked in the top five analysts during his time at the fund, said in response that the quality of AI was somewhere between that of an intern and a junior associate. Subsequent AI developments, including the launch of Claude's Fable model, have presumably made AI even more effective.

The skills that are important for analysts are similar to those for PMs. If you're able to use and interact with AI tools in a novel way compared to other candidates or members of your team, you'll stand a better chance of survival. Much like electronic trading firms, alternative data is becoming increasingly important, so being able to identify new data streams that can improve the success of a trading strategy will give you an edge, even if it's AI that does the grunt work. 

How AI is affecting quant jobs in hedge funds

Quant research, like investment analysis, is a role predicated on large scale analysis and AI is enabling this at faster speeds than ever before. Annanay Kapila, an ex-trader at Tower Research Capital, told us that Claude Fable is particularly good at identifying patterns in data. However, he also said that quant research as a profession has always had a particularly high bar for talent at elite firms and that the profile of a successful candidate won't change much beyond developing an ability to harness AI. One headhunter, speaking anonymously, told us "good quants will always be pretty safe... we've got a few more years before AI will be a real alpha generator."

One of the biggest changes in quant finance because of AI is a massive convergence of roles. The biggest development in recent years is that the roles of a quant developer and quant researcher are starting to merge, but the overall situation is more complex. Augusta Aiken, CEO of quant search firm AAA Global, told us last summer that the most desirable profile among hedge funds and trading firms is the 'quant-engineer-infra hybrid;' these quants can model a trading strategy, code the algorithms required to put that strategy into production and also contribute to the underlying systems that facilitate those trades. An ability to understand code and use AI coding tools is therefore increasingly important; quants relying solely on their mathematical expertise are now falling out of fashion.

How AI is affecting middle-office jobs in hedge funds

The middle office is one of the most at-risk sectors of banking and hedge funds are taking a similar approach. They're doing it more quietly than banks are (and aren't referring to these people as 'lower value human capital') but they're allegedly treating them even more harshly.

"Operations people who don’t code are being replaced with automation on a weekly basis," the headhunter told us. "Hundreds of ops guys who are not technical in any way being replaced, and a lot of them haven't found work in over a year." The headhunter said that "middle ground" employees are most at-risk here; senior employees have the experience to justify being kept on while younger employees are more likely to have embraced technology.

It's not just AI at fault here; the headhunter said there's also increased offshoring by major firms as "people are trying to keep costs low." This has been happening over a period of many years, but the quality of work done in these offshore centres is improving; "you don't need as much sanity checking as you did before."

Risk roles are a little different. Many top risk professionals in hedge funds are quants, so the changes to quant research are more akin to what's happening to their careers. Quant risk staff may see their roles converge with broader risk management functions, or they may be encouraged to take on more engineering responsibilities to build out the risk technology infrastructure.

How is AI affecting technology jobs in hedge funds?

No field has been affected more by AI than software engineering and development. Technology jobs in hedge funds are no exception to this. 

Umesh Subramanian said last October that AI is a "force multiplier" for engineers and it will place increased emphasis on engineers' ability to solve problems. The changes could also affect the interview process; rather than a singular three hour interview on a particular topic, Subramanian suggested that AI could be used across three separate hour-long interviews covering different topics "front to back" each time.

The convergence of roles can work both ways too; engineering staff can start taking on additional data science and quant research duties now that AI can automate some of the most time intensive aspects of their roles.

Some roles will be comparatively slow to adopt AI tools. Engineers working on low latency technologies like execution engines written in C++ are less likely to have AI write code for them due to the precise nature of their code and the massive negative repercussions of missing an AI-generated bug. Bjarne Stroustrup, inventor of C++ and a technical fellow at electronic trading firm Susquehanna, said earlier this year that AI-written low-latency C++ code is often more "bloated" and less secure.

There are also new roles being created to invent the AI tools everyone else is using. Balyasny's applied AI team had 20 researchers as of March. Hedge funds like Millennium and Qube Research, meanwhile are building out 'AI labs' designed to explore new applications of the technology in finance. For these roles, hedge funds are competing for talent directly with AI labs like Anthropic and OpenAI, and have to offer pretty hefty pay packages to tempt them over.

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