Will AI notetakers short-circuit or supercharge next-gen advisor training?

As the adoption of AI expands across all corners of the wealth space, from wirehouses to RIAs, there's a growing consensus that the technology can help firms get closer to the holy grail of growth: achieving greater productivity without sacrificing personalization.

But the increasing influence of technology also raises fresh questions about its human impact, including on next-gen advisors. 

Look no further than the 2024 Connected Wealth Report from Advisor360, which found one in five next-gen advisors with an average age of 36.5 years saw AI as a threat to their careers. Another 31 percent, it said, perceive AI as a threat to the advice sector at large.

A cautious embrace of AI

Shane Cummings, director of technology and cybersecurity at Halbert Hargrove, says his firm is taking a cautious approach to AI.

"We're trying to be really careful with how we do things from a data security perspective," Cummings told InvestmentNews. "What would make us the most efficient is if we could use it with client data, but we're still kind of on the fence as to whether we feel really safe doing that yet." 

Within its stack of approved tech platforms, Cummings says his firm is currently using Jump, an increasingly popular notetaking and meeting prep platform that announced a successful $20 million Series A funding round this month. There's also FP Alpha, a major player in AI-assisted financial planning, which he says saves associates time and effort by extracting essential information from estate, tax, and trust documents that can run dozens of pages long.

"Notetaking apps might save them a couple hours a week, just in terms of post-meeting notes and post-meeting follow-up.... Potentially more than that, depending on how many people they're meeting with," he says. "You can have a system ingest a tax return or property and casualty statements, and it can give you the output of all the key points that you know."

Era Jain, CEO and co-founder of wealth tech startup Zeplyn – which recently added a veteran of Merrill Lynch and LPL to its board – estimates its AI platform can save advisors at least 10 hours of work a week. It's designed to automate meeting preparation, notetaking, CRM updating, and other mundane tasks.

"When we started, we saw that the penetration of AI wasn't there. There was a lot of hesitancy," she says. "But now, we are at a point where 60 percent of financial advisors are either using AI [tools] or planning to use or integrate them over the next several years."

While next-gen advisors' role in the meeting room might have been to catalog and summarize points discussed, Jain says the advent of AI can enable them to do more high-value activities.

"Now the junior advisor has more time to actually engage with the client in the meeting," she says. "In my opinion, that's a much bigger enabler in terms of them learning and making their way up." 

Looking at other potential near-term use cases, Cummings envisions AI apps being able to extract data from client statements and migrating it into another system – to use in financial planning software or fill out account applications, for example. And while many younger advisors today are doing paraplanning work, he argues apps can be developed to do those jobs with AI instead.

Trust, but verify

While AI can take away a lot of heavy lifting, relying too much on the technology comes with risks. That includes hallucinations and incorrect inputs from false reads, which means junior advisors must still step in to double-check AI outputs, Cummings says.

"The advisor still needs to know what are the things to look out for, where it's still important to have that human judgment," he says.

"There are things the system can't tell you, like if a family has got their two sons as listed co-trustees, and it just so happens they're not getting along with each other right now....  The AI is not going to know that. So the advisor and their team should know that through their relationship with the client and speaking with them."

A new study by researchers at Microsoft and Carnegie Mellon University also suggests workers who rely excessively on generative AI run the risk of losing valuable critical thinking skills. As the paper highlighted: "[B]y mechanising routine tasks and leaving exception-handling to the human user, you deprive the user of the routine opportunities to practice their judgment and strengthen their cognitive musculature, leaving them atrophied and unprepared when the exceptions do arise."

To mitigate that threat in the advisory space, Cummings suggests young advisors should adopt a learning mindset, working up to the point where they can competently do higher-level analysis.

"Maybe that's through different types of education, or firms having different types of advisor training programs, or different ways that they can take in firm culture and how things are done," he says.

By enhancing advisors' ability to capture information about clients, Cummings and Jain agree AI tools have the potential to build a comprehensive history of the different relationships they have. If done correctly, it would have serious implications for advisor mentorship, as G2 and G3 advisors could get quickly caught up on priority concerns and milestone events for key clients.

"Conversations, little things that clients, their kids, and their grandkids care about ... [that's] not really stored in a CRM. It's in the advisor's head," Jain said. "That's where I think AI becomes so useful. They can actually help advisor transfer this information automatically into a centralized database and make it easier for the younger advisor to consume this data."