Majority of asset managers now use AI in investment operations, Mercer finds
More than half of asset managers have integrated artificial intelligence into at least one investment process, according to research by Mercer covering 131 firms worldwide. The industry has moved beyond early experimentation, though AI remains primarily a tool to enhance human productivity rather than replace human decision-making.
Fifty-five percent of respondents said their firms have deployed AI in active investment processes. Another 27% are running pilots or proof-of-concept projects. Only 18% have not yet integrated AI into their operations, yet 91% of all firms plan to increase AI use within the next 12 months.
Where asset managers are deploying AI
Operational efficiency drives most current adoption. Seventy-three percent of firms use AI to improve productivity in existing teams, automating routine work and freeing staff for higher-value tasks.
In investment work itself, 68% of firms use AI as a research partner, generating insights and analysis to support decision-making. Autonomous AI-where the system makes investment recommendations or executes trades without human approval-remains rare at just 5% of firms.
The disconnect between operational gains and investment returns is stark. While efficiency improvements are widespread, only 8% of firms reported measurable improvements in actual investment performance from AI implementation.
Data and regulation are the main obstacles
Two barriers dominate. Sixty-nine percent of asset managers cite data quality or access problems, while 59% point to regulatory and compliance concerns as obstacles to broader AI adoption.
Beverley Sharp, global manager research leader at Mercer, said: "AI is delivering measurable efficiency and insight for asset managers today, but the technology is largely a partner rather than a decision-maker. Addressing data, regulatory, and integration challenges will be essential to realise AI's broader potential in portfolio construction and execution."
Asset managers currently deploy AI upstream in the investment process-for research, idea generation, and analysis. Broader use in portfolio construction and trading execution depends on solving data and regulatory hurdles first.
For managers overseeing AI adoption in asset management firms, the priority is clear: tackle data governance and compliance frameworks before expecting AI to move beyond supporting human judgment.
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