In an industry marked by fierce competition and a constant pursuit of an edge, hedge funds have been relatively slow to incorporate artificial intelligence into their core operations. However, as advancements in AI technology continue to impress—sometimes even instill fear among businesses and government entities—the hedge fund sector is beginning to recognize its potential to replace one of its most significant assets: human investment talent. A number of former hedge fund professionals from reputable firms like Bridgewater are stepping into this new arena with startups aimed at leveraging AI.
Asset management firms, benefiting from substantial financial capabilities, have typically led the way in developing AI and machine-learning algorithms internally. Yet, their utilization of these technologies has largely focused on enhancing less glamorous functions such as regulatory compliance, legal verification, and technical support. Recently, however, the sophistication of large language models (LLMs) and AI agents has increased, instilling confidence in hedge funds that they can automate vital processes like research and analysis, traditionally managed by human experts.
Ken Griffin, the billionaire founder of Citadel, who once expressed skepticism about AI's market performance potential, recently shared at a Stanford event that he felt "fairly depressed" about the efficiency of the firm's AI agents. Griffin highlighted that tasks which previously required weeks of work from skilled employees can now be completed in just a few hours.
This technological evolution could level the playing field for smaller funds that lack near-unlimited resources, offering them a chance to disrupt the current dynamics of the hedge fund industry.
As competition intensifies, particularly over the last decade and a half, smaller hedge funds have faced mounting challenges. The increasing abundance of alternative data and complex risk models has favored larger institutions. However, Ian McInnis, the founder of Y-Combinator-backed WithAI, believes that LLMs can serve as a democratizing tool, empowering smaller firms to effectively analyze vast amounts of data.
McInnis, a former analyst at Bridgewater, is just one among a growing number of founders from established funds such as Schonfeld and Jain Global who are focused on integrating AI into investment practices. New companies like Macro Technologies, co-founded by Jaime Villa, aim to automate the repetitive tasks performed by macro analysts, while firms such as Serona Data, led by Cameron McKendrick, are working to extract investment signals from healthcare data—a process that previously relied heavily on human discretion.
These entrepreneurial endeavors tap into a clear demand within the industry for AI solutions capable of augmenting or even replacing traditional investment talent. Already, WithAI has secured four hedge fund clients, and McKendrick noted that his company produced its first dataset in collaboration with a major multistrategy manager.
This shift marks a significant transformation for hedge funds compared to just a year ago, when quant executives viewed AI favorably but still regarded human analysts as the key to maintaining the competitive edge in investing. Notably, Bridgewater’s recent collaboration with Mira Murati's Thinking Machine Labs aims to develop an LLM capable of evaluating financial texts with an expert level of judgment, reducing the need for human analysis of complex documents.
As AI technology becomes more prevalent, it may alleviate the intense competition for talent that has driven up operational costs in the hedge fund sector. The most significant expense for these firms typically stems from the salaries of skilled professionals—like portfolio managers and analysts. If tasks can be automated or outsourced, costs could be significantly reduced. For example, Claire Brown, founder of Aristides Capital, pointed out on social media that "90% of the answers that Claude generates in 5 minutes are better than most people could produce in an hour." She argued that the latest iteration of AI is as competent as a junior analyst who would command a salary exceeding $100,000 annually, while the monthly subscription for the AI service is a fraction of that cost.
Jan Szilagyi, CEO of AI platform Reflexivity and a former co-Chief Investment Officer at Lombard Odier, foresees AI soon being capable of independently selecting stocks as it learns from the behavior of human investors. Villa also emphasized his firm’s goal of replicating essential asset management workflows so that AI can execute them proficiently.
For Stephen Wu, the enhancements offered by AI could significantly scale his operations. As the founder of Carthage Capital—a $50 million hedge fund that employs a mix of quantitative and fundamental strategies—Wu has expressed an eagerness to leverage AI to broaden his trading capabilities. Currently, he manages a portfolio of 10 to 20 stocks, but with effective AI agents, he envisions trading hundreds more, demonstrating the vast potential for intuition and decision-making to be augmented by technology.
