Good morning, NREB readers.
As always, we’re here to keep real estate professionals informed while cutting out the fluff. Let’s get right into it.

Consider a buyer who sends you an AI-generated explanation of why a home looks like a good deal. It includes a market summary, a few numbers, and a confident conclusion.

Then comes the question: “Does this look right to you?”

That is a useful opening. The buyer has shown you what they are thinking about and the information shaping their expectations. Your response can help them understand which parts hold up and what still needs work.

Bank of America’s 2026 Homebuyer Insights Report found that 20% of prospective buyers and current homeowners surveyed had used AI tools or chatbots for homebuying research in the previous year. Among prospective buyers who used AI, common tasks included estimating costs, learning about the process, and researching markets or property values.

Home-search companies are building for these conversations, too. Zillow announced its AI mode in March, initially as a limited beta, connecting conversational search with listing data. Realtor.com announced RealAssist AI in June, also beginning with a limited beta, designed around questions about budgets, preferences, and homes.

Those announcements show why it is worth understanding the tools a client might encounter. A search can now involve asking follow-up questions and comparing explanations, alongside browsing listings.

For agents keeping up with how AI is changing the way clients find and interpret information, today’s partner provides a daily briefing on AI developments.

If you’re a decision maker at your company, you need to be on the bleeding edge of, well, everything. But before you go signing up for seminars, conferences, lunch ‘n learns, and all that jazz, just know there’s a far better (and simpler) way: Subscribing to The Deep View.

This daily newsletter condenses everything you need to know about the latest and greatest AI developments into a 5-minute read. Squeeze it into your morning coffee break and before you know it, you’ll be an expert too.

Subscribe right here. It’s totally free, wildly informative, and trusted by 600,000+ readers at Google, Meta, Microsoft, and beyond.

Before correcting a result, ask what the client was trying to figure out. Are they worried about overpaying? Trying to understand a term? Unsure whether a property deserves a showing?

The same AI response can matter differently depending on that question. A broad market summary might help someone get oriented. It provides much less support for choosing an offer price on a particular house.

Ask to see the original question, the relevant answer, and any sources it supplied. That gives you something specific to discuss, including assumptions the client may not have noticed.

A buyer who asked for “reasons this home is overpriced” gave the tool a different assignment from one who asked for evidence on both sides. Understanding the request helps you understand the result.

Imagine an AI summary calling a listing a bargain because its asking price is below the city’s median sale price.

The median could be accurate. The conclusion still needs support. A citywide figure can combine different neighborhoods, property types, sizes, and conditions. Being below that figure does not establish that this particular home is underpriced.

This is where your local work becomes useful: examine relevant comparable sales, the property’s condition, and the homes the buyer could choose instead.

Explain which comparison changes the picture. If the evidence supports the buyer’s initial impression, say so. If it does not, show what led you to a different view.

That gives the buyer a way to evaluate the claim. Simply saying that AI makes mistakes leaves the original argument unanswered.

“AI said” does not tell you where the information came from. A response drawing on listing data, a summary of a dated article, and an answer based on assumptions the user supplied deserve different follow-up questions.

Three details are particularly useful:

Knowing which tools can search, retrieve information, or work with supplied documents helps you ask better questions. It also helps you recognize useful research instead of treating every AI answer as the same thing.

You can apply the same approach when a seller brings an AI-generated price opinion. Welcome the research, then connect the discussion to evidence about the property and its competition.

At your next consultation, make room for a simple question: “What have you found so far that you’d like us to look at together?”

A client’s homework can reveal their priorities before you spend half the appointment guessing. Start there, and help them reach a conclusion they can explain and support.

Sources

View all NREB and NREB Premium articles here