AI is an increasingly important tool for hedge funds and asset managers operating in credit markets, but the tech is being used primarily to enhance investment processes rather than replace investment professionals, according to report by the Financial Times citing new research from Barclays.
A survey of 410 institutional investors across North America, Europe, the Middle East and Asia found that AI adoption has moved beyond the testing phase and is now becoming embedded in day-to-day investment activities. However, market participants largely view the technology as a productivity enhancer rather than a substitute for human decision-making.
Barclays strategists Zornitsa Todorova and Andrea Diaz Lafuente said respondents expect AI to reshape workflows and responsibilities across investment teams, but without triggering significant reductions in staffing levels in the near term.
Only a small minority of investors surveyed anticipate meaningful job cuts as a result of AI implementation, with most expecting headcount to remain broadly stable while efficiency improves.
Research emerged as the most common application of AI across the buy-side community. Among hedge funds, AI is most frequently used to support investment research, data analysis and idea generation, while modelling, risk assessment and security screening also ranked among the leading use cases.
The findings suggest that AI is currently serving as an analytical support tool rather than taking a central role in portfolio management or trading execution.
Adoption remains relatively limited in areas such as trade execution and portfolio construction. Most respondents across hedge funds, long-only managers and asset owners said AI currently plays only a minor role in trading activities, despite broader technological advances that continue to reshape fixed-income market structure.
The credit market has undergone a gradual shift towards greater electronic trading in recent years, mirroring developments long seen in equity markets. However, Barclays’ survey indicates that AI-driven trading remains at an early stage of adoption for most institutional investors.
Respondents identified data security and privacy concerns as the most significant barriers to wider AI deployment. Investors remain cautious about the handling of sensitive trading information, proprietary investment models and client data. Regulatory uncertainty, compliance requirements and organisational resistance to change were also cited as key challenges.
The survey found notable differences in adoption rates between investor groups, with hedge funds emerging as the most active users of AI technology.
According to the research, nearly three-quarters of hedge fund respondents reported using AI on a daily basis, significantly ahead of long-only asset managers and asset owners. Barclays attributed the gap to differences in operating models and investment objectives.
The bank noted that hedge funds typically run faster-moving strategies where speed of analysis and information processing can provide a competitive advantage. By comparison, asset owners tend to operate with longer investment horizons and more formalised decision-making frameworks, leading to a slower pace of adoption.
For hedge fund managers, the findings suggest that AI is increasingly becoming a standard component of the investment toolkit. While concerns about automation replacing human expertise continue to generate debate across financial markets, the survey indicates that, for now, investors see the technology as augmenting rather than displacing portfolio managers, analysts and traders.
As adoption continues to accelerate, the focus appears to be shifting from whether firms should embrace AI to how effectively they can integrate it into existing investment processes while managing the operational, regulatory and data-governance challenges that come with it.
