Advisors want client time; AI is buying back emails

Seventy-two percent of the 549 advisors Vanguard and Escalent polled for the Cogent Beat Advisor survey say the thing they most want is more time with prospective and current clients. That figure is the benchmark an advisory practice should use to judge an AI purchase this year, and the test is narrow: does the tool hand the desk more client-facing hours, or does it just finish the same work in less of them?

Reported usage sits a layer below that target, with advisors naming drafting emails (38%), research (35%) and meeting notes (27%) among their primary uses — administrative and productivity work, each one a way to finish an existing task faster rather than a way to open a new conversation. Goldman Sachs forecasts AI-related investment across all industries will reach $1 trillion this year, which makes the wealth-management share look small; it is buying minutes back, and how those minutes get redeployed is the part the numbers don't yet show.

Lauren Wilkinson, Vanguard's chief information officer of financial advisor services, has described the next step as moving from tools that assist with tasks to tools that automate them, which is where time for higher-value work would come from. The harder question is what the practice does with the hours once they are free, and Ric Edelman, who founded Edelman Financial Engines, has put the arithmetic plainly: a note-taking tool that saves 45 minutes after each client review meeting produces nothing for the P&L unless that time becomes another client meeting, another prospecting call or the capacity to serve more households.

That is the test for prospecting in particular: a firm with a live pipeline — a referral motion, a list of qualified prospects, a service model built to absorb more households — can turn a saved afternoon into revenue, while a firm without one will watch the same afternoon get absorbed by the work that filled it before. Deploying AI into service ahead of prospecting is likely the wrong order for a practice that wants to grow, because a service tool relieves the pressure a full pipeline would simply reapply, and capacity that isn't pointed at a prospect doesn't compound.

Julie Littlechild, founder and CEO of Absolute Engagement, argues the larger prize sits past efficiency: using AI to understand clients at a deeper level, identify how they change over time and surface needs and opportunities nobody has asked about yet — the difference between a meeting that runs smoothly and one the client remembers. That is both the better case for the technology and the harder build, since it requires feeding client data into a system and acting on what comes back, which is the ground the SEC's still-forming AI guidance covers.

Two days ago this publication noted AssetMark's survey, which put advisor AI adoption at 85% and the time savings at four hours a week while leaving the error rate unquantified and naming compliance as the stuck point. Read together, the two surveys say adoption is no longer the constraint; the redeployment of hours is, and written policies that name a human in the loop over AI processes are the practical first move while the SEC's expectations take shape.

The next benchmark worth reading will be a usage question that names prospecting outright, because only when advisors report spending reclaimed hours there will the 72% show up as a return.