Wealth managers keen to stay relevant in the age of artificial intelligence may soon find that clients with a mere $1 million in liquid assets are no longer worth spending human hours on.
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“The mass-affluent client now gets something close to private-banking quality from AI,” said Debasish Patnaik, senior partner McKinsey. That not only “strips the value from the advisor whose role was standardized advice,” but it also means “the kind of person hired into wealth management changes fundamentally,” he said in an interview.
The assessment implies that individuals with liquid assets between $100,000 and $1,000,000 — broadly defined as the mass affluent within the industry — could soon be handed over to AI. Instead, human wealth managers keen to show they can do better than AI need to focus their talents on the emotional needs of the truly rich, Patnaik’s analysis implies.
The prediction comes as financial professionals everywhere struggle to interpret how AI will upend their careers. Signals from the industry and those advising it, meanwhile, aren’t always consistent. And in wealth management, there are even signs that AI is creating hiring needs as firms seize on the promise of extra productivity to expand.
Citigroup plans to recruit hundreds of humans for its private banking and wealth management business as it deploys AI. That’s as CEO Jane Fraser has made it an explicit goal for the bank to become a “global leader in wealth management.”
Citi says it wants to add 400 wealth advisors across its U.S. retail bank and another 100 staffers for its private bank. At the same time, the Wall Street bank is developing AI-backed software aimed at helping it produce near-instant reviews of portfolios at scale, down from the several hours such tasks take today.
Bankers will be able to “press a button” in order to instantly “draft an email from the chief investment officer and distill what it means for the client,” Joe Bonanno, Citi’s head of wealth intelligence, said in an interview.
Among products being rolled out by Citi are a conversational AI-powered avatar specifically intended to support rich clients on issues such as how to manage their child’s college fund. The upshot overall is that AI will let Citi have more contact with its customers, and “engagement keeps clients happier and stickier,” Bonanno said.
Read More: To gain wallet share, Citi to add 400 U.S. advisors and personal bankers
Patnaik says that when it comes to handling ultra-wealthy clients, it helps if a manager has the emotional nous to deal with tense situations such as deciding which family member gets to inherit what, or being there to hold their hand through a market rout.
The advisor who successfully “reads the room” and “manages family dynamics” will have the best chance of surviving the onslaught of AI, Patnaik said. They need to be willing to “sit with a client through a succession or a liquidity event, and help them think clearly. AI does not touch that, so firms will weight hiring heavily toward it.”
Professionals in the industry, where senior managers handling ultra-high-net-worth clients can earn millions of dollars a year, are trying to figure out what exactly makes a human advisor irreplaceable by AI. That’s as the list of AI products continues to grow. Anthropic’s Claude, OpenAI’s ChatGPT and Alphabet’s Gemini already offer tools that allow users to model portfolios, optimize taxation and even explore possible philanthropic ventures.
Banks are also developing their own platforms. At Group AG, the world’s largest wealth manager, 90% of its advisory teams in the US are already using an internal AI platform to help make them more productive. UBS private bankers and wealth managers now get personalized insights on clients courtesy of the in-house AI tool the firm uses, according to a spokesperson.
The Swiss bank is applying AI to improve areas like advisor productivity and operational efficiency, while at the same time prioritizing governance, transparency and trust, the spokesperson said.
In fact, AI’s arrival now appears to be creating a need for new kinds of human expertise, such as AI governance. Patnaik says firms will likely increasingly need to rely on “specialists, behavioral data scientists, personalization architects, and human-in-the-loop oversight professionals.”
These are “entirely new roles” that “did not exist in wealth management a few years ago,” he said. “These hybrid profiles, combining domain expertise with technical fluency, are among the fastest growing and hardest to fill anywhere in financial services.”
