Blog: The AI-Enabled Client

The Meeting Before the Meeting

How AI is changing what clients expect from their advisor

By Dan Daum, CEO and Co-Founder of WealthStream

Imagine a client who has been with your firm for 15 years. She never misses a review. She referred her sister. Her adult children work with you, too. Let's call her Margaret.

It's Monday night. Margaret is at her kitchen table with a glass of wine, her laptop, and the recommendation you sent last week. Your meeting is tomorrow. She puts the recommendation into ChatGPT and starts asking questions.

What am I missing? What could go wrong? What should I push back on?

Some answers are useful. Some may be wrong. But each one gives her another question, and she keeps going. She can admit she doesn't understand. She can ask the same thing three times. She can explore a concern she hasn't quite figured out how to raise with you.

By the time Margaret walks into your office, she has already had a meeting about your advice. She's arriving with a point of view.

I think this is one of the most consequential changes AI brings to wealth management. We spend a lot of time discussing what it will do for advisors. We need to spend more time thinking about what it changes for clients.

The meeting changes before the relationship does

Clients have always sought second opinions. There was usually an accountant, a friend, or a brother-in-law with strong views and varying qualifications. What has changed is how easy it is to get one, privately, whenever a question occurs to you.

Margaret doesn't have to believe everything AI tells her. One plausible alternative is enough to change the conversation.

HSBC's 2026 U.S. investor research captures this well. In a survey conducted by Ipsos of 1,128 affluent and high-net-worth investors, 57% said they use AI for financial and investment tasks. Only 7% named AI as the most influential factor in their last investment decision. Meanwhile, 77% cited a need for reassurance from an advisor.

My read is that AI can influence the conversation long before a client trusts it to make the decision. Someone can use it extensively and still want their advisor's judgment.

That's why healthy retention can give firms an incomplete picture. Margaret can keep every account with you while quietly checking every recommendation. The assets haven't moved. Her expectations have.

Show what changes the answer

Now imagine Margaret opening the meeting with this: "ChatGPT says I can start gifting to my children without putting my retirement at risk. Why are you recommending that I wait?"

It's a fair question. From her perspective, she has two reasonable answers. Your job is to help her understand what accounts for the difference.

Suppose she gave AI her portfolio balance and current spending. You also know she is considering retiring earlier than planned, and she may need to help pay for her mother's care. Those details could change how much flexibility she needs. They belong in the analysis before she commits to a gift.

A reasonable answer to a narrow question can still be the wrong advice for the client.

The useful response makes the reasoning visible: here's what that answer assumes, here's what else we need to account for, and here's why it changes the recommendation. Knowing the client matters when you can show what that knowledge changes.

And we should be honest about the other possibility. The client may have found something worth considering. An assumption may need updating. An alternative may be better. If the question improves the advice, that's a good outcome. Being willing to revisit your recommendation is part of earning trust.

Knowing the client has to show up in the work

We should also be careful with the reassurance that AI will never understand the client. AI can work with context when it's given that context. I wouldn't build a firm's future on the assumption that the technology will stay where it is today.

The responsibility is to build a full picture of the household, ask what's missing, and connect decisions across the client's life. A gifting question may involve retirement income, family obligations, and estate planning. Clients should be able to see how those considerations shaped the advice.

Then someone has to see it through: coordinate with the accountant and attorney, help the client act, and revisit the decision when life changes. That's where accountability shows up.

This is central to why we're building WealthStream. We believe every client deserves advice that reflects the complexity of their life. Our Advice Intelligence helps advisors identify planning opportunities across a client's financial life and understand why they matter. Advisors use that work to decide what fits the client and explain why.

Prepare for the conversation the client has already had

Before your next meeting, look at the recommendation from the client's side. Using your firm's approved tools and data policies, explore the alternatives an AI conversation might surface. Ask what could be missing from your own analysis. Work through the questions you would find hardest to answer.

Then practice explaining the recommendation in plain language. What did you consider? Why does this approach fit? What would change your mind? If you struggle to make the reasoning clear, you have something useful to work on before the client arrives.

In the meeting, invite the other perspective: "Have you come across anything that made you think about this differently?" Make it easy for the client to bring the question into the room. A concern left unspoken is much harder to address.

I see a real opportunity here. A client who arrives curious, engaged, and ready to ask better questions gives you more to work with. That conversation can deepen the relationship, provided you are prepared to have it.

AI raises the burden to demonstrate the value of advice. Margaret still wants your help. Make sure she can see why it matters.