Hedge funds have spent the last few years building AI tools that analyze data faster and more thoroughly than any human team could. The technology is now reshaping every major role in the industry - from portfolio managers who use AI to replicate senior analysts' work, to middle office staff being replaced by automation on a weekly basis. For management professionals, the question is no longer whether AI will affect their teams, but how to lead through the transition.
OpenAI revealed in March that 95% of investment teams at Balyasny use 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. The fund's merger arbitrage team has AI agents that proactively search for filings from companies involved in M&A deals to continuously re-evaluate positions. Citadel rolled out its own AI tool for equities traders last year, which highlights risk and generates reading lists based on each trader's portfolio.
Portfolio managers and analysts face the biggest shift
Ken Griffin, Citadel's founder, said in May that complex research which would take finance PhDs weeks to complete can now be done by AI agents in days. That places increased pressure on portfolio managers to translate AI-generated insights into actual profit. Knowing how to use these systems is becoming an increasingly important part of portfolio management jobs.
Investment analysts are among the most exposed roles across any industry, according to an Anthropic report from March. 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, said the quality of AI was somewhere between that of an intern and a junior associate - and subsequent AI developments have presumably made it even more effective.
For analysts, the skills that matter are similar to those for PMs. Being able to use and interact with AI tools in a novel way compared to other candidates or team members will improve your chances of survival. Alternative data is becoming increasingly important, so identifying new data streams that can improve a trading strategy gives you an edge, even if AI does the grunt work.
Quants, middle office, and risk
Quant research has always had a high bar for talent at elite firms, and the profile of a successful candidate won't change much beyond developing an ability to harness AI. One headhunter told us: "good quants will always be pretty safe... we've got a few more years before AI will be a real alpha generator."
The bigger change is a convergence of roles. Quant developers and quant researchers are starting to merge, and the most desirable profile among hedge funds and trading firms is the "quant-engineer-infra hybrid" - someone who can model a trading strategy, code the algorithms required to put it into production, and contribute to the underlying systems that facilitate trades. Quants relying solely on their mathematical expertise are falling out of fashion.
The middle office is one of the most at-risk sectors. "Operations people who don't code are being replaced with automation on a weekly basis," the headhunter said. "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 "middle ground" employees are most at risk; senior employees have the experience to justify being kept on, while younger employees are more likely to have embraced technology. Increased offshoring is compounding the pressure as firms try to keep costs low.
Risk roles are a little different. Many top risk professionals in hedge funds are quants, so they face similar changes to their quant research colleagues. 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.
Technology roles and the new AI jobs
No field has been affected more by AI than software engineering. Umesh Subramanian, Citadel's former CTO, said last October that AI is a "force multiplier" for engineers and will place increased emphasis on their ability to solve problems. He suggested the interview process could shift from a single three-hour session on one topic to three separate hour-long interviews covering different topics "front to back" each time.
Some roles will be comparatively slow to adopt AI. 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 the 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.
New roles are also being created to invent the AI tools everyone else is using. Balyasny's applied AI team had 20 researchers as of March. Funds like Millennium and Qube Research are building "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 hefty pay packages to tempt people over.
Why this matters for management professionals
The pattern across all these roles is consistent: AI is not eliminating jobs wholesale, but it is changing the skill profile of every position on the team. Managers who understand what these tools can and cannot do will make better decisions about restructuring, hiring, and training. The convergence of technical and analytical roles - the quant-engineer-infra hybrid, the analyst who can build AI workflows - suggests that siloed job descriptions are becoming less useful. Management professionals who want to stay ahead of these changes can explore AI for Finance training to understand the specific tools reshaping their industry, or broader AI for Management courses to learn how to lead teams through this transition.
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