AI is the capacity answer to the advisor shortage

The advisory profession is about to run a math problem it cannot staff its way out of: in the next ten years, 38% of advisors controlling 42% of industry assets retire, McKinsey projects a 100,000-person shortfall by 2034, and fee-based revenue jumped from $150 billion in 2015 to $260 billion in 2024. More demand, fewer hands.

Financial Advisor Magazine's 2025 RIA Survey and Ranking makes the case that artificial intelligence is the next major player in the advisory space, and the coverage leaves the Terminator scenario aside. What it describes is the unglamorous layer where advisors already work with AI: taking notes from client meetings, fighting cybercrime, flipping through statements for planning opportunities. Machines will talk to other machines about how to help clients, the survey argues, and humans will be needed to clean up after them.

The stakes are high enough that the survey opens with a warning about pace: Brent Brodeski, founder and CEO of Savant Wealth Management in Rockford, Illinois, argues that unified fintech and account consolidation will completely transform the industry in three to five years. In previous technology waves, he says, there were first adopters and fast followers; this time even the fast followers will have trouble catching up. "It used to take 100 years to change, right? Or 50 years," he says, and now the changes happen in five, with winners determined in three.

Whether that three-year clock is exactly right, the direction is defensible, and the implication for a practice is sharper than the prediction. The adoption that matters sits in the preparation layer where an advisor's minutes actually go, not in a client-facing chatbot. Susie Cranston, president and COO of Cresset in Chicago, makes the point in the survey coverage: note-taking is the visible use, but it just scratches the surface. The real leverage sits in the work an advisor does before a meeting—assembling current statements, pulling investment returns, preparing for an onboarding—and that, she says, can all be automated.

Test Brodeski's point about fast followers against your own roadmap: in past software cycles, a firm could lag by a release and still buy the mature version at a discount, but if this wave is as fast as he argues, a slow rollout stops being deferral and becomes the thing that defines the firm's next decade. The firms already running statements through an AI layer have a head start a competitor cannot buy in a single budget cycle.

This publication has argued before that the succession wave will be won by firms with the capacity to absorb books of business, and AI is the mechanism that makes that capacity real. If the preparation work of onboarding a client drops from hours to minutes, a firm can take on more client relationships without a proportional increase in headcount. The same tools that scan a prospect's statements for planning opportunities are the ones that let a small team service a book that previously took two advisors.

The survey's ranking list will draw the clicks, but the adoption findings are the part worth reading twice: a five-person RIA does not need to know where it stands in the AUM rankings; it needs to know how much advisor time still goes to data assembly. The survey coverage makes a related point about the data itself—the lakes are getting huge, and the firms that win will be the ones with the security and data integrity to make that data usable. Transcription programs make mistakes, which is why the human in the loop is the reliability feature.

The coverage also holds a prospecting promise: it imagines a future where, with AI's help, advisors find clients rather than the other way around, which is the same preparation insight applied earlier in the sales cycle. The first meeting is won on the statement review and the planning gap it reveals, and that is work AI can do while the advisor decides who to call. The advisor's job shifts from assembling information to delivering judgment on it.

Read practically, the survey describes a division of labor in which machines compile, secure, and flag while humans trust, judge, and build the relationship. With a third of the profession retiring and fee-based revenue still climbing, the only way that math adds up is for the machine side of the division to grow. Brodeski's three-year clock is already running.