The wealthiest investors in America are no longer experimenting with artificial intelligence. They are using it for their everyday needs – even for money matters.
That is the central finding of a new study from BNY Wealth, which surveyed 251 ultra-high-net-worth individuals on how AI is reshaping their financial lives. The study found 96% use AI personally at least once a week, while 89% invest in companies with significant AI exposure and 54% are already using AI to inform financial decision-making.
For Kevin Shea, a director and senior equity strategist at BNY Wealth in New York – who has spent more than two decades covering the technology and communication sectors – the shift from AI as a curiosity to a core technology is unquestionable.
"AI has definitively gone mainstream with ultra-high-net-worth clients," Shea told InvestmentNews. "It's in their personal lives, their professional lives, their financial lives. It's moved from this interesting tool to now a core technology that they're actually using."
For Shea, the rise of AI is only natural given the past two decades of productivity tools helping people make more educated decisions.
"AI is that natural progression," he says. "It is great at taking a lot of distributed data, simplifying very complex scenarios and giving context in areas where you might not be an expert."
The BNY Wealth report – conducted by The Harris Poll on a pool of respondents with at least $10 million in investable assets – found 83% of UHNW individuals already use AI-driven tools to inform their investment choices, including one in 10 saying their decisions are already primarily AI-led. The most common financial application is investment research, cited by 76% of respondents, followed by portfolio analytics at 63%.
For the advisors at BNY Wealth, Shea says the productivity gains have been transformative.
"My group is 6x more productive today than it was two years ago," he said. "We're able to engage with our clients more frequently, and we use AI to help aggregate an incredible amount of data as it relates to investment opportunities. We're able to articulate our views on companies or industries and put together these views at a much faster pace than what we would have been able to do without AI."
As Shea tells it, portfolio managers and wealth advisors using AI-augmented tools can now identify exposures to interest rate volatility, currency risk, emerging market movements, and other potential vulnerabilities with a precision and velocity that was simply not possible before.
One upshot of the AI boom is how clients are now walking into meetings with more knowledge than they used to. While Shea sees it as a largely positive step, but acknowledges the new demands that come with it.
"When I go into meetings and we're talking about these new IPOs, these new innovative companies, they've been able to interact with AI and have far more detailed conversations than five years ago, where they would have just read an article about that," he said.
More than a third of UHNW investors in the BNY Wealth study say AI has made their relationships with wealth managers more data-driven, and 25% say they have become more collaborative. Importantly, Shea says, that means better-informed clients are still turning to advisors to check the robot's work.
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"Even though AI provides an incredible amount of data and information that wasn't there before, expertise on our side is even more important today than it was before," he said.
Part of the problem, according to Shea, is how the large language models underpinning AI models are usually built to be agreeable when given certain prompts or following a user's train of questioning. State-of-the-art models may be getting better, but that hasn't stripped out the occasional misleading answer, inaccurate takeaway, or hallucination in AI chats that go long or far enough.
"That's what builds trust and transparency – knowing I have an expert that has 25 years of experience and I can bounce these ideas off of him," Shea said. "Even though people were worried that expertise would get commoditized or automated with AI, what we've seen so far is that expertise has become even more important in today's AI era."
The BNY Wealth report supports that point, as a full 94% of UHNW respondents believe AI is most effective when paired with human judgment, and 91% say they need to understand how AI reaches its conclusions before acting on them.
Privacy is one of the most significant friction points in the BNY Wealth study, which found 57% of UHNW investors believe AI makes wealth management less transparent, while a nearly equal 56% remain concerned about data misuse; that's even as 72% said they have confidence in the security of data shared with AI financial tools.
Like other firms on Wall Street, BNY Wealth built its own proprietary AI platform, Eliza – named after the wife of its founder Alexander Hamilton. Shea said the platform leverages multiple AI models depending on the task, while keeping client data protected within a secure, governed environment. "We know that when we use our model, even if we leverage [third-party AI models], that [the external providers] do not use client data to teach their models," Shea said.
To verify model outputs and keep AI honest, Shea's best practice is to mark every number and strong statement it spits out, then double-check those items. For other people, he says the strategy has been to build a cabinet of AI models that they can consult and fact-check against each other.
Educating clients on the limits of AI is also part of the work. For Shea, its ascendance as a go-to-resource echoes the rise of WebMD in the early days of the internet.
"Everybody thought that they were their own personal doctor. We're kind of having a resurgence of that – except AI can go to any topic," he said. "But there are still doctors today, even though WebMD has been around for a long time."
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