Your Next Home Search Might Start With AI. Here’s Where It Should End.

Before many buyers ever call an agent or talk to a lender, they’ve already asked a chatbot a few questions. What can I afford? What would my monthly payment look like? Which neighborhoods fit my budget?

That’s not a fringe habit anymore. Artificial intelligence is quietly working its way into nearly every stage of buying a home, from the first search to the final loan approval. Some of that is good news for buyers. Some of it needs a second look. Here’s what’s changing and how to make the technology work for you rather than the other way around.

Buyers are already using it, especially younger ones

According to Bank of America’s 2026 homebuyer insights report, as cited by Homes.com, about one in five prospective buyers and homeowners turned to AI tools or chatbots during the past year while researching a purchase. The number climbs with younger generations: 28% of millennials and 32% of Gen Z said they’d used it.

Most people aren’t asking AI to pick a house for them. They’re using it to run early numbers on affordability and closing costs, to understand how the buying process works, and to get a feel for neighborhoods and property values. In other words, it’s becoming the homework phase.

Searching is changing too. Instead of clicking through filters for price, bedrooms and ZIP code, buyers are starting to describe what they want in plain language and let the tool narrow things down. The main payoff is time, since fewer listings need to be sorted by hand before the real search begins.

The number on the screen isn’t the whole story

If you’ve ever looked up a home online, you’ve seen an instant value estimate. Those figures come from automated valuation models, or AVMs: software that combines recent sales, tax records, property details and neighborhood trends to produce a number.

They’ve gotten more accurate over the years, and they’re useful for a quick read. But they lean heavily on “comps,” which are similar nearby homes that sold recently. When there are plenty of those, the estimate tends to be reasonable. When there aren’t, it can drift.

That matters here on the coast. Waterfront and soundfront homes, older cottages with years of updates, properties on larger rural lots and one-of-a-kind builds are exactly the kinds of homes algorithms find hardest to price. Software also can’t see a brand-new kitchen, a roof that’s near the end of its life, or the difference between two houses on the same street when one has the better view. Treat an online estimate as a conversation starter, then ask your agent how it compares to what has actually sold nearby.

Getting a mortgage is getting faster

Behind the scenes, lenders are adopting AI quickly. Consulting firm Stratmor Group found that 38% of mortgage lenders were using AI or machine learning in underwriting in 2024, compared with 15% the year before. Instead of someone manually combing through bank statements and tax returns, software can pull out the key details in a fraction of the time.

The savings add up. Freddie Mac has reported that machine-learning tools in its underwriting platform can cut up to $1,500 in costs per loan and shave about five days off the process.

There’s also a fairness angle. Lenders can now look beyond a single credit score at things like cash flow and regular bill payments. In 2026, Fannie Mae and Freddie Mac also began rolling out newer scoring models, including VantageScore 4.0, which can factor in rent-payment history. For some buyers, especially first-timers with a thin credit file or self-employed borrowers with irregular income, that fuller picture could make a real difference.

Where people still matter most

For all the speed, buying a home is still one of the biggest financial decisions most people make, and the National Association of Realtors reports that most buyers still work with an agent to get there.

AI can summarize data, but it doesn’t know your priorities, your comfort level with a monthly payment, or how long you plan to stay. It can’t walk a property, notice water stains on a ceiling, or tell you how a neighborhood feels at 5 p.m. on a weekday. And it can simply be wrong.

How to use AI the smart way

Use it early: comparing areas, testing budgets, building a shortlist. Then verify. Cross-check what it tells you about schools, commutes and neighborhoods with local sources, and go see places in person.

When you apply for a loan, it’s fair to ask your lender whether AI plays a role in underwriting, what information it considers, and whether a person reviews the file before a final decision. If you’re sharing financial details with any online tool, make sure it’s run by a licensed lender or broker and check its privacy policy.

And when a price or estimate doesn’t add up, bring it to your agent. That’s where local knowledge earns its keep.

Thinking about buying or selling along coastal North Carolina and want a second set of eyes on what the online numbers are telling you? My team is happy to walk through it with you, no pressure, just straight answers.