The changes that artificial intelligence has brought to the industry over the past few years have arrived hard and fast, forcing wealth management firms of all sizes to consider how to best implement the newly available tools.
For many decision makers, that has meant thinking through the potential compliance implications and triaging in order to decide which AI tasks to tackle first. That was the focus of "From Ideas to Impact: Driving AI Adoption Across Your Firm," a session at Financial Planning's
While their approaches differed, all the firms recognized the importance of bringing compliance into the AI conversation early on.
Bringing compliance in from the ground floor
If a wealth management firm were a car, compliance would be the brake pedal, said Abusaid, who added that his firm recognized that reality at the outset when it came to implementing AI.
"We figured, 'Let's not waste time coming up with great ideas and have compliance shut them down,'" he said. "So our compliance officers are part of the conversation."
At RFG Advisory, Hutchison said they split the data architecture into corporate and advisor platform pieces, each with its own technology stack. For advisors, the firm's tools have a more narrow or "endpoint specific" focus, he said.
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On the corporate
"That has a compliant ecosystem there, where our compliance team can interact a lot more seamlessly," he said.
Ranking AI implementation tasks
Halbert Hargrove began its AI journey by ranking tasks AI could be used for from lowest to highest risk, said Abusaid. Unsurprisingly, first in line — the lowest risk task — was an AI note-taker. The firm
Next up were dashboards, which have been built but are yet to be rolled out to advisors, said Abusaid.
One area that the firm has avoided using AI for is investment management, Abusaid said. However, the firm has delved into AI to support its marketing efforts.
"We stuck our neck out," he said. "I was nervous, but I had to let it happen."
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As fellow ADVISE AI speaker
Taking note of this change in the AI adoption panel, Abusaid said his firm reached out to clients in search of feedback.
"That went great, by the way," he said. "So if you do a good job, it'll pan out. You might get one or two clients who decide they want an issue. And we did, by the way, but we addressed it."
Vanguard's Bell said his firm's AI implementation has been split into three waves. The first started about five years ago, with machine learning and predictive analytics for prospecting, portfolio construction optimization techniques and financial planning.
The second wave began about two years ago, with the introduction of ChatGPT and generative AI, said Bell.
"Like everybody else, we saw that there's a bunch of productivity use cases that are now unlocked," he said.
These included advisor, operations, sales, marketing and software development assistance, said Bell.
"It's been a frantic two years, unlocking some of the capabilities that these new tools give us," he said.
Bell said they now sit on the precipice of a third wave, which involves moving beyond advisor productivity and more into efficacy. This includes coaching from the insights gleaned from recorded client conversations, he said.
"They can improve the advice that they deliver, and ultimately the outcomes for clients," he said.
