Investors Are Asking AI Before They Ask You

When I started in this industry, my grandparents were on Facebook, and today they are using ChatGPT, which says most of what needs to be said about where client expectations are headed. 

Thirty years ago advisors held an advantage because the data, the products, and the planning math were out of reach for the average investor. That advantage began to erode when robo-advisors and platforms like Robinhood arrived after the financial crisis. Today, anyone can get a thoughtful answer in seconds, and McKinsey's Vlad Golyk reports that one-third of consumers across age groups are now turning to tools like Claude and ChatGPT for investment guidance, in many cases before they ever meet with a human advisor.

Information is a commodity, and so is the process built on top of it. The calculations, the scenario modeling, and the financial planning math that once defined the profession can be reproduced on a cell phone, and a growing number of clients are using AI to check an advisor's work as it happens. 

Demand for advice has not fallen as a result, with SEC-registered investment advisers reporting roughly 12 percent more individual clients in 2025 than in 2023, but what clients expect from the person across the table has changed completely.

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Where the value lives now

If information and analysis are both table stakes, the value moves to four things AI cannot replicate on its own. 

1. Context - This means knowing how to ask the right questions and assemble the entire universe around a client, including the accounts held elsewhere, the business interests, the family dynamics, and the goals the client has never written down. AI can only work with what it is given, and the advisor who knows what to ask for is the one who sees the whole picture.

2. Relationship - The personal connection is built over years through consistency and candor, it is the reason a client will believe an advisor over a confident answer from a chatbot. In a world of entirely digital engagements, people are starting to appreciate human connection again, which makes the advisor who sits across the table from a client more valuable instead of less.

3. Emotional stewardship - Boxer Mike Tyson famously said, "Everybody has a plan until they get punched in the mouth." Investing works the same way, because every client has a plan until they feel real downside, or a big life change, or some shift in their picture, and at that point the math stops mattering and they make emotional decisions. AI can tell a client what the numbers recommend. It cannot sit with them through the tie between money and emotion, and it is far less capable of understanding the full web of people inside a multigenerational relationship, where spouses, children, and grandchildren each bring their own history and expectations to the same pool of wealth.

4. Tax efficiency - Taxes are one of the clearest ways an advisor earns back the fee a client pays. The general rules of taxation are available to anyone with a chat window, but the value sits in how those rules interact with a specific portfolio and a specific life, where decisions about gains and losses, distributions, charitable giving, concentrated positions, and retirement income all affect one another and often have to be coordinated with an accountant or attorney. AI can surface a technically sound strategy, but realizing it takes tax lot level detail, timing, and follow through, and the advisor who owns that complexity delivers a result the client can see on paper.

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The talent shortage rewards the advisors who care

Cerulli research finds that 35 percent of financial advisors, managing 40 percent of industry assets, plan to retire within the next decade, a gap I covered at length in “Are You Prepared for the Advisor Mass Exodus?”. 

Firms cannot hire their way out of a shortage that size, and the advisors who remain will be serving clients who arrive more informed and more demanding than ever. The advisors who genuinely care about their clients and give consistently good advice will keep winning in that environment, because they are doing the work AI cannot do, and the firms that equip them well will capture the assets that are about to change hands.

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Human advice requires a real-time data foundation

An advisor’s advantage only holds if he or she has a complete and current view of the client at the moment a decision is being made. Picture a client who spent the previous evening workshopping a sector rotation with Claude and now arrives convinced their portfolio is overexposed to technology. Now, consider two versions of what happens next. 

In the first, the advisor knows the client well, but holdings sit in one system, performance in another, and cost basis still has to be reconciled, so the advisor cannot quantify the consequences or guide the client with confidence in the room. They take notes and promise to follow up, and the client leaves having had a more useful conversation with Claude the night before than with their advisor that morning.

The relationship was there, but the infrastructure to make it actionable was not, and that is the cost of a fragmented stack where every handoff adds another reconciliation step and every step adds delay.

In the second version, the advisor opens a real-time view of the household and sees current sector exposure, drift from target, the risk impact of the proposed rotation, and which tax lots could be sold to limit the gain, along with upcoming cash needs and recent conversations. With that context the advisor can go past validating or rejecting the idea and ask why the client wants to act now, whether it reflects a real change in goals or a reaction to recent headlines, and what the tradeoffs look like in terms the client can feel, which turns a plausible idea into a deliberate decision.

A unified, real-time foundation makes that second meeting possible by removing the context switching and the reconciliation between systems, so that a transaction persists across the entire experience the moment it happens. It is also what allows AI to work from the full picture instead of leaving the advisor responsible for supplying context every time.

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Clients shouldn't be the only ones using AI

The same technology raising client expectations should be working on the advisor's side of the table, starting with the work that fills a calendar without ever deepening a relationship. Meeting preparation, note taking, follow up drafting, and the routine mechanics of service consume a large share of every advisor's week, and because software can now do that work faster and more consistently, firms that still staff it with people are paying a premium for something clients no longer value. The question for firm leaders is what to do with the time that comes back, and my answer is to spend nearly all of it on the client.

The larger opportunity is that AI can act as a memory for the relationship. No advisor can carry the full history of every household in their head, including the daughter's wedding, the concentrated stock position, the offhand comment about selling the business someday, and the worry voiced two meetings ago, but AI working from a firm's real-time data can hold all of it and bring the right piece forward at the right moment. That is how an advisor arrives already knowing what has changed for a client and what may be on their mind, and reaches out before the client has to ask. Clients are using AI to become better informed, and advisors should be using it to become closer, because that level of attention is the one thing a chatbot cannot offer.

Clients will keep arriving with AI-generated ideas, and public information will never again be a meaningful advantage. The firms that win will be the ones whose advisors use AI to handle the commodity work and to know their clients better, so they can spend their time on trust, judgment, and the moments when money gets personal.