A seller sits down with three agents. Each one gives their pitch. Then the seller goes and feeds all three transcripts into ChatGPT and asks it to compare them.
Which agent had the most specific results? Which one talked about client experience as a substitute for data? Which one actually answered the hard questions?
This is not a hypothetical. It is the direction the market is heading, and most agents have not put a lot of thought into how it impacts client decision making.
In a recent episode of their weekly sales and marketing show, Andrew Fogliato and Taylor Hack got into what AI means for a working real estate business right now and not just the hype version, not the fear version, the practical one.
The client scrutiny problem
Fogliato and Hack were direct about where this is going. Clients are already running agent communications through AI tools. Emails, comparables, market analyses. The agents who rely on warmth and personality without results to back it up are going to get flagged.
“They’re going to record all three agents they interview for a listing and get Claude to analyze the three of them,” Hack said. “There are agents that talk a lot about client experience because they don’t have results. There are agents that talk a lot about results.”
The response is not to try to manipulate the output. It is to ask AI what a client should look for when hiring an agent, what questions they should ask, and what red flags to watch for, then build your process around actually meeting that criteria.
“If anybody is using these systems to analyze this, we will be ready for the test in advance,” Hack said.
Where AI is actually saving time
Fogliato has been testing Claude extensively after years on ChatGPT. The difference he found is not in what the tools tell you but in what they find that you would not have found yourself.
He fed Google Analytics data, Google Search Console data and Screaming Frog SEO reports into Claude together and had it build a unified action plan. Technical analysis that previously took eight to 20 hours now takes about 90 minutes of back and forth. An SEO audit that would have been six months of work two years ago was completed in a day and a half.
He also built a custom analytics dashboard in an afternoon that pulls data from every platform REM uses into one place, with AI analysis built in. The tool he had been looking for at the enterprise level, priced at roughly $10,000 a month, he built himself in three hours.
For ad campaigns, feeding 800 campaigns worth of data into Claude produced a concrete finding: Thursday is the best day to launch Meta lead form ads, outperforming the next closest day by 20 per cent on cost per lead.
Why the AI insight that looked right was completely wrong
Not everything Claude surfaces is actionable. The same analysis that found the Thursday pattern also recommended publishing more content between 10 a.m. and 2 p.m. because articles in that window get significantly more views.
Fogliato caught the problem immediately. All regular articles go out before that window. The only content that lands between 10 and 2 is breaking news, which gets shared heavily because it matters. The window was not better. The content type was different.
“You can make data say anything you want. You still have to use your head with anything it gives you,” he said.
This is where expertise still wins. An operator who knows the business will consistently outperform someone who reads AI output without context.
The right way to think about AI in your business
Hack drew a clear line. AI belongs on the back end – the parts of the job that consume time without producing client contact. Not the conversion side. Not the relationship side.
Fogliato used DocuSign as the parallel. When it launched, some experienced agents resisted it because they thought it would reduce time with clients. The agents who used it correctly freed up drive time and got more of it.
“If you’re using it correctly, does this give you more time with clients? That’s how you should look at AI,” Fogliato said. “If you don’t want to do that and you’re just taking stuff off your plate so you can sit around more, you’re not going to increase your revenue.”
The agents who will struggle are the ones using AI to avoid picking up the phone, not the ones using it to make more calls possible.
One practical thing agents can use right now
Claude’s desktop app includes a feature called Dispatch that allows it to operate your computer remotely. While at his daughter’s basketball game, Fogliato had a client who needed a file from his desktop. He dispatched Claude to find the file and send it to the client through Slack without touching his computer.
Hack called it the most immediately useful thing discussed in the episode. The ability to handle a client need in real time without interrupting what you are doing is a direct service win.
For agents not ready for that level, the starting point is simpler. Use AI to handle the analysis and administrative work that currently eats hours. Put that time back into client relationships. That is where the revenue is.
The full episode covers how to set up Claude so it improves over time, why junior employees should be paying close attention to this shift, and what the AI landscape looks like across ChatGPT, Claude and Gemini. Watch now:
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Content by REM Bot has been created with the assistance of AI. Audio and video interviews, conducted by our team with real people, are transcribed and repurposed into text for those who prefer reading. REM Bot articles are reviewed by staff before publication to ensure factual accuracy and maintain editorial standards.
