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Opinions February 23, 2026
How AI Is Changing Fund Management
Artificial intelligence is impacting all facets of advisers’ work, right down to the explanations they share with clients.
Reported by Marta Zarraga
Marta Zarraga
For decades, technology inside asset management was largely invisible to clients. It powered accounting, trading and reporting, but it rarely shaped the conversations advisers had with plan sponsors or participants. Artificial intelligence is changing that dynamic. As AI becomes embedded in how investment teams conduct research, manage risk and run their organizations, its impact is increasingly visible in the products advisers evaluate and the way asset managers engage with them.
From my perspective as a chief information officer at a research-driven investment firm, this shift is not a break from fundamental investing. It is an evolution in how information is processed and insight is delivered. The philosophy remains human-led, and the tools are becoming more powerful.
Expanding the Reach of Fundamental Research
One of the most immediate uses of AI—already being implemented—is in investment research, where the challenge is scale, rather than access. Our investment professionals must absorb vast amounts of information, such as company filings, earnings calls, news flow, economic data and industry research across global markets.
AI helps investment teams navigate that volume more efficiently. Natural-language processing tools can scan and summarize lengthy documents, flag changes in language or tone across company communications and surface themes that warrant deeper analysis. This allows analysts and portfolio managers to spend less time searching for information and more time debating implications and applying judgment.
These tools do not make investment decisions. They function as research workhorses, accelerating discovery while leaving conclusions firmly in human hands.
Turning Complexity Into Clearer Explanations
AI also influences fund management by helping investment teams explain products and portfolios more clearly. As strategies grow more global and markets more complex, translating investment decisions into understandable narratives has become increasingly important.
AI helps rapidly synthesize complex portfolio and product information into clearer, more accessible explanations for clients. AI-enabled tools connect product performance back to underlying drivers, such as company fundamentals, sector exposures or macroeconomic forces, making it easier for investment teams and distribution partners to articulate what is happening and why.
For advisers, this can improve the quality of conversations with plan sponsors and participants. Clearer explanations support better understanding, particularly during periods of market stress, when questions are more frequent and confidence matters most. In this way, technology helps us deliver key insights with greater speed and clarity.
Freeing Up Time
Much of the early value of AI has come from operational efficiency. Plan advisers are increasingly seeing the effects as embedded AI tackles tasks like classifying and routing information, sharing meeting insights, preparing for meetings and supporting decisionmaking. Distribution teams respond faster, provide clearer explanations of portfolio behavior and tailor information more effectively for different audiences, ranging from plan committees to participant-focused communications.
As their time spent doing repetitive and time-consuming tasks is reduced, advisers are gaining capacity to focus on higher-value work. This creates more time for what technology cannot replace: building relationships, understanding client needs and exercising judgment in moments that matter.
In this sense, AI is not about diminishing the adviser’s role. It is about supporting it, by handling more of the mechanical work behind the scenes so attention can remain focused on people.
Over time, this raises expectations. Faster responses, more transparent discussions and richer investment-outcome-related context are becoming more common. Adviser-manager interactions are evolving not because advice itself is changing, but because the information supporting that advice is more timely, transparent and driven by data.
Why Governance Matters
As AI becomes more embedded in investment processes, governance has moved from a technical concern to a strategic priority. Data quality, privacy, model behavior and oversight directly affect the reliability of insights and the trust placed in them.
AI adoption needs to go hand-in-hand with strong controls: clear accountability; rigorous testing and validation; continuous monitoring; and human oversight at critical decision points. These disciplines help ensure that technology enhances judgment, rather than obscures it.
For advisers evaluating asset managers, governance practices are becoming an increasingly visible part of due diligence. How a firm manages AI-related risk can reflect how it approaches risk management more broadly.
As AI moves from the engine room to the front line, the fundamentals remain unchanged—long-term thinking, disciplined processes, governance, human judgment and oversight—but the balance of innovation and responsibility will matter more than ever for asset managers, advisers and the investors we ultimately serve.Marta Zarraga is the global chief information officer at Capital Group Companies Inc., where she oversees technology and cybersecurity.
This feature is to provide general information only, does not constitute legal or tax advice, and cannot be used or substituted for legal or tax advice. Any opinions of the author do not necessarily reflect the stance of ISS STOXX or its affiliates.
