How money managers are transforming AI solutions from experimental to practical |
Liam O’Sullivan remembers what it was like for fixed income asset managers before technology started taking over.
When his firm RP Investment Advisors began doing business in 2009, portfolio managers had to manually look through pricing runs from dealers and write down buying and selling opportunities on the back of an envelope alongside a calculation of the transaction’s impact to the portfolio, says the principal and co-head of client and product solutions.
“It’s quite amazing how far the industry has come in 17 years.”
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Artificial intelligence solutions in money management are transforming from experimental to practical, with nine out of 10 managers confirming current or planned AI use, according to Mercer’s 2024 survey of its global investment manager database. Indeed, the survey found almost half of respondents were using large language models (44 per cent) or machine learning models (48 per cent).
• 73% of asset management industry executives said AI is critical to their organization’s future.
• 77% said they have an effective AI strategy and roadmap in place.
• 18% planned to use agentic AI over the next three years.
• 12% reported seeing no returns or negative ROI from AI.
Source: Grant Thornton survey, December 2025
The pursuit of investment strategy edge is one of the factors driving the adoption of AI in money management, says Alpesh Sethia, chief technology officer at the Healthcare of Ontario Pension Plan.
Money managers are at the forefront of the adoption of novel artificial intelligence solutions as they transform from experimental to practical
“I’ve talked to many asset managers and, often, that edge is something where they invest heavily in data science within their organization to make sure they’re looking at data the right way, processing it the right way and putting it into the lens of what their portfolio looks like to manage it.”
The novelty of AI may still surprise some people, but to O’Sullivan, the technology is an off-shoot of the ongoing work of active managers.
“In the fixed income world, [it] came as a logical progression from what we and some others [were] doing before, which is using computing power to sift through data to try to find signals before other people could find them.”
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RPIA’s system makes suggestions to portfolio managers, highlights anomalies and shows new issues that could be potentially priced in for an asset.
At Mackenzie Investments, AI tools are most predominantly used by the quantitative equity team and the systematic team in its multi-strategy group, according to........