November 09, 2026
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Andrew Janian discusses how Citadel is applying AI across the firm and why human judgment and adaptation remain central.
As artificial intelligence becomes embedded across Citadel, from operational workflows to the investment process, our primary concern is figuring out how to use it well. For Andrew Janian, Senior Advisor at Citadel, that entails giving teams room to experiment around problems rather than tools and preserving judgment in the most consequential parts of the investment process.
At Bloomberg’s 2026 Enterprise Data & Tech Summit, Andrew joined Gregory Bond, Chief Investment Officer at Man Group, and Aaron Linsky, Head of Engineering for Alpha Engine and founding CTO of AIA Labs at Bridgewater Associates, for the “Leaders Dialogue: AI Across the Investment Lifecycle” panel, moderated by Angana Jacob, Head of Research Data at Bloomberg.
Andrew described an approach to AI that lets individual teams develop tools for the problems they’re solving, while centralizing capabilities that can give the firm a competitive advantage.
He pointed to applications across Citadel and Citadel Securities, ranging from agents tasked with reconciling trades and diagnosing discrepancies to tools investment teams develop to support specific research workflows.
As models and providers advance, Andrew said that the firm is designed to adapt quickly rather than anchoring teams to a particular model or tool.
“We’re trying to focus people on what they are working on and not the tools that they’re using,” Andrew said.
The same operating model creates opportunity for the people closest to the work because investors and technologists can build and test new approaches around the problems they know best.
As the tools become more capable, the boundaries between investing and technology may blur further, making people who can combine domain expertise with curiosity, technical fluency and strong judgment especially valuable.
Although AI can accelerate parts of the investment process, Andrew cautioned against outsourcing certain aspects of an investor’s job.
He pointed to portfolio managers using AI to challenge their own thinking by testing an investment thesis, preparing for a management meeting or asking it to develop the strongest argument against an existing view.
“Be my counter thesis and debate,” Andrew said, describing how some PMs engage with the technology. “I see great PMs that will go back and forth, having this thing truly try to dispute them.” In some cases, he noted, that process can inspire an investor to change direction.
Andrew also argued that fundamental investors may be particularly well-equipped to work with imperfect AI outputs because their day-to-day work already involves evaluating incomplete or conflicting information. And in markets, some of the most critical questions can’t be resolved through historical backtesting because new events may have no precedent in the data.
Andrew compared AI to the emergence of alternative datasets. Early access can create an advantage, but widespread availability eventually levels the playing field. Once access is universal, edge depends on how well teams apply the tools to real problems and judge what they produce.
“I think edge is a cultural thing,” Andrew said. “Can you continue to push yourself and continue to evolve?”
“To us, this is just another tool,” he added. “We’re just constantly trying to say, can we continue to make use of this and stay at the forefront?”
