Author: Coach Emily

Do Home Buyers Use ChatGPT to Find a Real Estate Agent?

Written by Coach Emily on October 5, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

Home buyers use ChatGPT to research the market, but most still choose a real estate agent through a referral. Bank of America found 20% of prospective buyers and homeowners have used AI for homebuying research, while NAR reports 43% of buyers hired a referred agent. This guide shows how AI now vets the referral, and how to pass that check.

Key Takeaways

Buyers mostly use ChatGPT early in the process, for affordability, process questions, and neighborhood research, not as the final hiring decision.
Referrals still choose the agent: 43% of buyers used a referred agent and 18% used an agent they’d worked with before, according to NAR’s 2025 Profile of Home Buyers and Sellers.
A ChatGPT answer can confirm or undercut a referral, and it draws almost entirely from your own website and Google Business Profile.
Portal profiles don’t carry over into AI answers; one 2026 study found zero Zillow citations across 1,567 ChatGPT sources.
AI visibility is a documentation problem: publish verifiable numbers in the places AI actually reads.

What does it mean when home buyers use ChatGPT to find an agent?

When home buyers use ChatGPT to find a real estate agent, they’re doing one of two things. They’re either asking it to recommend agents in a market, or they’re asking it about a specific agent someone already named. The first replaces a Google search. The second replaces a background check.

Most agents only think about the first. I’d argue the second matters more, because the hiring decision still starts with a person, not a prompt.

Why this matters for real estate agents

AI is already part of how buyers get informed. According to Realtor.com (October 2025), 82% of recent and prospective buyers and sellers use AI for housing market information, and ChatGPT is the most-used platform at 67%.

Research isn’t the same as hiring, though. According to NAR’s 2025 Profile of Home Buyers and Sellers, 43% of buyers used an agent they found through a referral, and another 18% went back to an agent they’d worked with before. That’s 61% of buyers choosing their agent through a relationship.

Here’s the thing nobody wants to tell you: a referral doesn’t carry the whole decision anymore. A buyer who hears your name at a backyard barbecue can ask ChatGPT about you before they ever text you. If the answer is thin, generic, or names three other agents instead, you can lose a referral you already earned.

The upside is real too. NAR reported on a Denver agent who won a $1.7 million listing after a seller found him through a Gemini search. By the time they spoke, the AI’s summary of his credentials and content had already built the trust.

“…when it comes to high-stakes decisions, people still want trusted experts by their side.”
— Matt Vernon, Head of Consumer Lending, Bank of America (via NAR, June 2026)

How are home buyers using ChatGPT in the agent decision?

What are buyers actually asking ChatGPT?

They’re mostly asking early-stage questions about money, process, and place. According to Bank of America’s 2026 Homebuyer Insights Report, as covered by NAR, 20% of prospective buyers and current homeowners have used AI for homebuying research. That rises to 28% of millennials and 32% of Gen Z. Those buyers most often used AI to estimate affordability and closing costs, learn the buying process, and research neighborhoods.

Notice what’s missing from that list: “Who should I hire?” Buyers use AI to get smart before they talk to anyone. For an agent who publishes useful answers, that’s an opening.

Does ChatGPT replace the referral?

No. It audits the referral. Relationships still account for 61% of buyer-agent matches in NAR’s data. The same Realtor.com survey found consumers rated real estate agents the most accurate source of market information, ahead of AI.

What’s changed is the step between hearing your name and calling you. That step can now run through a chat window, and you don’t get to see the answer the buyer got.

What does ChatGPT read before it names an agent?

It reads the things you own. In Omni Eclipse’s 2026 analysis of 334 ChatGPT answers to real estate buying queries, ChatGPT named a median of six businesses per city. 98% of the sources it cited were the agent’s own website or Google Business Profile. In U.S. markets, roughly three of every four named slots went to an individual agent or a named team rather than a brokerage brand.

Treat that as one vendor study, not settled science. It still points at the two assets you control completely.

How do you make ChatGPT confirm your referrals?

Treat AI visibility as a documentation system, not a marketing campaign. These four steps are scalable and repeatable, and none of them requires a new platform.

Step 1: Run the referral test on yourself

Your baseline is what a referred buyer sees today. Open ChatGPT, Gemini, and Perplexity and ask two questions: “Best real estate agent in [your neighborhood]” and “Tell me about [your full name], real estate agent in [your city].” Screenshot every answer. Note which facts appear, what’s wrong or missing, and which sources are linked. Repeat the test on the first Monday of every month.

Step 2: Treat your Google Business Profile as infrastructure

Your Google Business Profile is the single largest source ChatGPT cited for real estate recommendations in the Omni Eclipse data. Complete every field, confirm your service areas, and build review volume on purpose. Review counts were the justification ChatGPT attached to agent picks most often.

Don’t leave review requests to memory. Trigger them automatically from your CRM when a deal closes. In Follow Up Boss, that’s an action plan tied to the closed stage.

Step 3: Put your numbers on your own website

AI quotes numbers and skips adjectives. Replace “trusted local expert” on your about page with your transaction count, sales volume, years licensed, neighborhoods served, and review total. If your production data lives in MLS, export it and let AI draft the summary. I walk through that workflow in How to Integrate AI With MLS Systems. Update the page every quarter.

Step 4: Answer the questions buyers ask AI first

Publish content that answers the research-stage questions buyers are already typing into ChatGPT: affordability, process, and neighborhoods. Put it under your name, on your site, with question-based headings and direct answers in the first sentence. Video counts too, because transcripts are indexable text. That’s why YouTube Shorts belong in this system.

A compliance note: your website and Google Business Profile are advertising. In Texas, TREC’s advertising rule (22 TAC 535.155) requires your broker’s name on it. The FTC’s rule on consumer reviews and testimonials (16 CFR Part 465) prohibits fake reviews and buying positive ones. This is general information, not legal advice. Confirm the specifics with your broker.

Common mistakes

Quoting vendor statistics as fact. Some widely shared figures claiming that roughly two-thirds of buyers now pick agents through AI come from companies that sell AI visibility services. Use NAR, bank, and portal survey data in your listing presentations. Your credibility is on the line every time you cite a number.

Assuming your Zillow reviews cover you. Portal profiles still generate leads, but they didn’t show up as cited sources in the Omni Eclipse data. Your AI presence is your website and your Google Business Profile.

Leaning on your brokerage’s brand. ChatGPT answers “best agent in [city]” with people and teams far more often than company names. Your brokerage page isn’t your personal footprint.

Writing adjectives instead of numbers. “Dedicated” and “experienced” give AI nothing to quote. “112 homes sold in Stone Oak since 2019” does.

Testing once and calling it done. AI answers shift month to month. A single screenshot tells you nothing about the trend.

Frequently Asked Questions

Do home buyers use ChatGPT to find a real estate agent?

Some do, but most don’t use it as the deciding factor. Bank of America found 20% of prospective buyers and current homeowners have used AI tools for homebuying research, mostly for affordability, process education, and neighborhood research. The agent decision still runs largely through referrals, and a ChatGPT answer can either support that referral or undercut it.

What percentage of home buyers use AI in their home search?

Estimates range from 20% to 82%, depending on how the question is asked. Bank of America’s 2026 Homebuyer Insights Report found 20% of prospective buyers and homeowners have used AI for homebuying research. A Realtor.com survey of 1,000 recent and prospective buyers and sellers found 82% use AI for housing market information, with ChatGPT the most-used tool at 67%.

How do buyers usually find their real estate agent?

Most buyers find their agent through people they trust. According to NAR’s 2025 Profile of Home Buyers and Sellers, 43% of buyers used an agent they found through a referral, and 18% used an agent they had worked with before. Together, that’s 61% of buyers choosing an agent through a relationship rather than a search engine, portal, or chatbot.

How does ChatGPT decide which real estate agents to recommend?

ChatGPT relies on sources the agent controls. In Omni Eclipse’s 2026 study of 334 ChatGPT answers, 98% of cited sources were the agent’s own website or Google Business Profile. The answers most often justified picks with review counts, years in business, and sales volume, which means specific, verifiable numbers carry more weight than marketing adjectives.

Does my Zillow profile help me show up in ChatGPT?

Not directly, based on current evidence. Omni Eclipse’s 2026 analysis of 1,567 ChatGPT citations for real estate buying queries found zero citations to Zillow, Realtor.com, Redfin, or Trulia. Portals still drive leads and traffic, but a strong portal profile doesn’t transfer to AI visibility. Your own website and Google Business Profile do the work there.

How can a real estate agent check whether ChatGPT recommends them?

Ask the questions your clients ask. Open ChatGPT, Gemini, and Perplexity and type “best real estate agent in [your neighborhood]” and “tell me about [your name], real estate agent in [your city].” Record whether you appear, what facts are cited, and which sources are linked. Repeat monthly, because AI answers change more often than Google rankings.

Bring this to your team or event

Emily Terrell speaks at brokerage events, real estate conferences, and team trainings on AI, systems, and social media — the exact playbook in this post, delivered live to your audience. As a Top Coach and Speaker at Tom Ferry International and an active agent closing 70+ transactions a year, Emily speaks from the stage about what’s working right now, not theory. Recent stages include NAHREP and eXp Con. See her keynote topics.

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

For real estate agents who want to implement this: Get the weekly real estate prompt library at weeklyrealestateprompts.com or follow @coachemilyterrell on Instagram for daily systems and AI breakdowns.

AI Consultant vs. Real Estate Coach: Which Should You Hire?

Written by Coach Emily on October 5, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

In the AI consultant vs. real estate coach decision, the consultant fits a build problem: a custom integration, data pipeline, or brokerage-wide rollout with a defined deliverable. An AI-focused coach fits an adoption problem: the tools exist, but nobody uses them consistently. This guide gives you a five-question diagnostic to tell which one you have.

Key Takeaways

An AI consultant solves build problems: integrations, data connections, and platform rollouts with a defined deliverable and an end date.
An AI-focused real estate coach solves adoption problems: tools that already exist but aren’t producing results because they aren’t used consistently.
Most individual agents have an adoption problem, which matches NAR’s finding that 46% of Realtors say AI hasn’t noticeably changed their business.
Brokerages rolling out a new platform often need both, in sequence: consultant first, coach second.
If no workflow is written down yet, document one before you hire anyone.

What is the difference between an AI consultant and an AI real estate coach?

An AI consultant builds something. An AI-focused real estate coach changes how people work. The consultant’s engagement ends with a deliverable: a connected system, a configured platform, a documented integration. The coach’s engagement produces a behavior: agents who use the tools every week, on real listings and real clients, inside a compliant workflow.

Both are legitimate hires. They solve different problems, and paying one to solve the other’s problem is the most expensive AI mistake I see agents and brokerages make.

Why does the AI consultant vs. real estate coach decision matter?

Here’s the thing nobody wants to say out loud: most agents already have the tools. What they don’t have is results. According to NAR’s 2025 Technology Survey (September 2025), 46% of Realtors said AI had no noticeable impact on their business, and only 17% reported a significantly positive impact.

That gap isn’t a software problem. It’s a usage problem. And spending keeps climbing anyway: the same survey found 24% of agents spend more than $500 a month on technology tools.

The stakes are higher for teams and brokerages. According to NAR’s 2026 Member Profile (June 2026), 21% of Realtors now work on teams, and team-based brokerage specialists reported a median of 32 transaction sides, compared with nine for the typical individual agent. At that volume, a broken handoff between your lead source and your CRM costs real deals. So does automation your agents quietly stop using.

How do you know whether you have a build problem or an adoption problem?

Answer these five questions honestly. Mostly “build” answers point to a consultant. Mostly “adoption” answers point to a coach. A split usually means you need both, in sequence.

Does the tool you need already exist?

If it doesn’t exist off the shelf, you have a build problem. A custom connection between your listing data, your website, and your CRM is a build. If the tool exists (ChatGPT, Claude, the AI features inside Follow Up Boss) and you still aren’t getting results, you have an adoption problem.

Is the finished product a system or a behavior?

“A working lead-routing integration” is a system. “Every agent drafts a listing copy with AI and reviews it for Fair Housing language before it posts” is a behavior. Consultants deliver the first. Coaches deliver the second.

Does the work end, or does it repeat every week?

A build has a finish line. Adoption doesn’t. It’s a weekly habit that decays without accountability, and if the problem shows up again every Monday, a one-time project won’t hold it.

Who has to change: your software or your people?

If the software changes and nobody’s workday changes, you’ve bought a build. If people have to work differently, someone has to own that change past launch day.

Is anything written down yet?

If you can’t hand someone a one-page description of the workflow you want, neither hire will get far. A consultant can’t build an undefined process, and a coach will spend the first month writing it down with you.

When is an AI consultant the better hire?

I’m a coach, so read this section knowing that. I’d give you the same answer if you hired me. Hire a consultant when:

You need a technical integration. Connecting listing data across your MLS, website, and CRM runs through standards like the RESO Web API, which replaced the older RETS transport. That’s engineering work with licensing rules attached, not a coaching topic. I covered the compliant routes in how to integrate AI with MLS systems.
You’re rolling out a platform across a brokerage. Security review, user permissions, data handling, and vendor contracts are consultant territory.
You need something custom built. An internal tool, a reporting dashboard, or a lead-scoring model trained on your own transaction history.

In each case, the deliverable is concrete, the scope is definable, and the engagement should end.

When is an AI-focused real estate coach the better hire?

Hire a coach when the tools work and the results don’t. The signs are consistent:

You’ve paid for AI tools for six months and can’t name the hours they save you.
One agent on the team uses AI well, and nobody else does.
Prompts live in someone’s head or a notes app, not a shared library.
AI output never reaches the CRM. It gets drafted, copied, and lost.
Nobody reviews AI-written listing copy against Fair Housing and TREC advertising rules before it posts.

None of those are build problems. They’re behavior problems, and behavior changes with repetition and accountability, not a handoff document. It’s the same reason AI training for real estate agents has to include a live build on the agent’s own listing instead of a tool tour.

“A consultant hands you a system on the last day of the contract. A coach is still there in week six, when your team quietly stops using it. Know which week you’re paying for.”
— Emily Terrell, Tom Ferry Coach

What if you don’t need either one yet?

Some agents are one step earlier. If you can’t name the single workflow you want AI to run, don’t hire anyone this month.

Pick one repetitive task (past-client follow-up, listing descriptions, showing feedback) and write down every step you take today. That document is the brief a consultant needs and the starting point a coach would build with you. It costs nothing, and it tells you which hire you actually need.

Start with the work around your listings, where automation carries the least risk. My breakdown of what agents can automate around the MLS is a good place to pick your first workflow.

How I use this in my own business

My team closes 70+ transactions a year in about five hours a week of my active management, and the AI side of that runs on one rule: nothing gets automated until it’s written down.

When we added AI-drafted past-client follow-up inside Follow Up Boss, I had both problems at once. The setup took an afternoon. That was the build. Getting every agent to review, personalize, and send those drafts consistently took six weeks of weekly check-ins. That was adoption.

If I’d hired a consultant for the whole thing, I’d have paid for a clean automation nobody used. If I’d hired only a coach, we’d have spent sessions working around a system that wasn’t connected. Knowing which half was which is what made it work. It’s also the lens I use with every agent I coach at Tom Ferry International.

Common mistakes

Hiring a consultant to fix a habit. A perfectly built automation doesn’t make anyone open it. If your problem is consistency, a deliverable won’t solve it.

Hiring a coach to build infrastructure. Coaching sessions spent troubleshooting data feeds are expensive sessions. If the system doesn’t exist yet, build it first.

Buying a new tool before auditing the old ones. Before you add anything, list every AI subscription you pay for and the specific task each one handles. Cancel whatever you can’t match to a task.

Measuring launch instead of usage. “The tool is live” isn’t a result. “Every agent used it on every new listing this month” is.

Skipping the client data question. Whoever you hire, ask how client records are handled and where they’re stored. Pasting a client’s contact or financial details into a consumer chatbot is a decision with consequences.

Frequently Asked Questions

What does an AI consultant do for a real estate business?

An AI consultant builds or configures a specific system: a CRM integration, a lead-routing automation, an MLS data connection, or a brokerage-wide tool rollout. The engagement has a defined scope, deliverable, and end date. Consultants are strongest on technical architecture and weakest on the part that follows handoff, which is getting agents to use the system every week.

What does an AI real estate coach do?

An AI-focused real estate coach changes how you and your team work with tools you already have. That means building prompts on your own listings, wiring outputs into your CRM, setting review standards for Fair Housing and advertising compliance, and holding the team accountable week over week. The deliverable is consistent behavior, not software.

How much does an AI consultant cost compared to a real estate coach?

Pricing varies too widely to quote a reliable average, so compare the structure instead. Consultants typically bill per project or per hour for a defined build. Coaching is usually a recurring monthly engagement. Before you compare prices, write down what you expect to own when the engagement ends: a working system, a changed team, or both.

Can I hire both an AI consultant and a coach?

Yes, and for brokerages rolling out a new platform, that’s often the right sequence. Hire the consultant first to build and connect the system, then bring in a coach or trainer to drive adoption. Reverse the order and the coach spends sessions working around missing infrastructure. Keep the scopes separate so neither is paid to do the other’s job.

Should a solo agent hire an AI consultant?

Rarely. Most solo agents don’t have a build problem, because the tools they need, like ChatGPT, Claude, and the AI features inside their CRM, already exist off the shelf. What solo agents usually lack is a documented workflow and the consistency to run it. That’s an adoption problem, and a consultant’s deliverable won’t fix it.

What questions should I ask before hiring AI help for my brokerage?

Ask what you’ll own on the last day of the engagement, who maintains the system after handoff, how client data is handled and stored, and how success will be measured 90 days later. If the answer to the last question is ‘the tool is live,’ you’re buying a build. If it’s ‘agents use it weekly,’ you’re buying adoption.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

Is an AI Keynote Worth It for Real Estate Brokerages?

Written by Coach Emily on October 5, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. Speaker for NAHREP, eXp Con, and brokerages nationwide.

An AI keynote for real estate is worth it only when it’s built as the start of an adoption system, not a standalone event. According to NAR’s 2025 Technology Survey, 46% of Realtors say AI has had no noticeable impact on their business. This guide covers the five requirements that turn a keynote into daily agent usage.

Key Takeaways

An AI keynote on its own changes what agents believe. It rarely changes what they do on Monday.
Most agents already use AI, so the gap a keynote has to close is impact, not awareness.
The keynotes worth booking include a live build on agents’ own listings and leads.
Every agent should leave with saved prompts, one named workflow, and a check-in date.
Pick the 30-day usage metric before you sign the speaker contract, not after the event.

What is an AI keynote for real estate?

An AI keynote for real estate is a stage presentation that shows agents how artificial intelligence applies to their business: listing marketing, lead follow-up, content, and client communication. The format ranges from a pure demonstration to a hybrid session where agents build a working workflow on their own devices. That range is the whole question. The format you book determines whether anything changes after the event.

Why does this matter for brokerage leaders?

Awareness isn’t your problem anymore. According to NAR’s 2025 Technology Survey, 20% of Realtors use AI tools daily, 22% weekly, and 27% a few times a month, while 32% haven’t used AI in their business at all (NAR, 2025).

The impact numbers are where it gets uncomfortable. The same survey found only 17% of Realtors report a significantly positive impact from AI, while 46% report no noticeable impact at all. HousingWire’s coverage of the survey flagged the same gap: widespread implementation, thin results.

It isn’t a software problem either. Two out of three agents agree or strongly agree that their brokerage provides all the tech tools they need, according to the NAR 2025 Technology Survey. Your agents have the tools. What they don’t have is a workflow that connects those tools to a listing, a lead, or a follow-up. One more inspiring hour on stage doesn’t build that.

Here’s the thing nobody wants to tell you: if you book an AI keynote and nothing is attached to it, you’ve bought a good afternoon. That has real value for culture. It isn’t worth the fee if your goal is adoption.

“At the heart of it all remains the trusted relationship between the agent and client.”
— Jessica Lautz, Deputy Chief Economist, National Association of Realtors

That’s the right frame for AI adoption. The tools exist to give agents time back for the relationship, not to add another screen they feel behind on.

What should a brokerage require before booking an AI keynote?

Five requirements separate a keynote that produces usage from one that produces applause. If a speaker can’t commit to all five, you’re booking entertainment.

Will agents build something on their own material?

The session needs a live build where every agent opens a real listing or a real lead and produces something usable before they leave. Watching a speaker build a listing marketing suite produces admiration. Building it yourself, on your own listing, produces the first use, and the first use is what makes a second one likely. I break down the full session format in AI training for real estate agents: what it must cover.

Do agents leave with the prompts already saved?

Every prompt shown on stage should be in the agent’s hands, saved in their AI tool, notes app, or a shared library, before they reach the parking lot. A prompt on a slide is gone by Tuesday. Ask the speaker exactly how prompts get delivered: a QR code to a library, a shared document, or a template agent’s copy during the session.

Is the session built around one workflow, not ten tools?

One named workflow beats a tour of ten tools, because agents adopt routines, not software. Pick the workflow that matches your brokerage’s biggest leak: listing marketing, speed-to-lead follow-up, or database content. A keynote that covers five AI platforms, three video tools, and a CRM integration in 60 minutes hands agents a longer list of things to feel behind on.

Is the 30-day follow-through on the calendar before the event?

The keynote is the kickoff. The follow-through is where adoption actually happens. Put two touchpoints on the calendar before the event: a short virtual implementation session around day 14 and a results check at day 30. Assign an internal champion, usually a team lead or a tech-forward agent, who owns the reminders and collects wins in between.

What number will you measure at day 30?

Choose the usage metric before you sign the contract, so the speaker designs the session toward it. Strong metrics are observable: the share of new listings with AI-assisted marketing, the share of new leads receiving follow-up within an hour, or the number of agents who used the saved prompt at least once. A post-event satisfaction survey measures the afternoon, not the adoption.

How I use this in my own business

I don’t teach anything from the stage that I’m not running in my own business. My team closes 70+ transactions a year in San Antonio on roughly five hours of active management a week. That only works because every repeatable task (listing marketing, follow-up, content) runs on a documented workflow instead of on someone remembering to do it.

When I build a full listing marketing suite live, the property description, social captions, email, and video script all come from one set of listing facts in about two minutes. I build it on a real listing because the room needs to see the workflow, not just the output. The output is impressive. The workflow is what they can repeat on Monday.

Common mistakes brokerages make with AI keynotes

Booking a tool tour. Ten tools in sixty minutes leaves agents overwhelmed and adopting none of them.
Scheduling it as the last session of the day. Energy is low, laptops are packed, and the build never happens.
Skipping the pre-work. Agents who arrive without logged-in, tested accounts lose the first 15 minutes to password resets.
Measuring the room’s energy. Applause and survey scores tell you the session was enjoyable, not that anything is still running at day 30.
Treating compliance as a closing slide. AI-generated listing copy is still advertising and can carry Fair Housing exposure, so the review step belongs inside the workflow. This is general information, not legal advice. Confirm requirements with your broker or attorney.

Frequently Asked Questions

Is an AI keynote worth it if agents won’t use the tools afterward?

Not on its own. A keynote that ends when the speaker leaves the stage changes what agents believe, not what they do. It’s worth the investment when it includes a live build on agents’ own material, saved prompts, one named workflow, and a 30-day follow-through with a usage metric you chose before booking.

What’s the difference between an AI keynote and AI training for real estate agents?

A keynote is built to shift how agents think about AI; training is built to install a workflow they’ll run the next day. The structural test is simple: if agents build something on their own listings or leads during the session, it’s training. The strongest format is a hybrid: keynote framing followed by a hands-on build.

How long should an AI keynote for real estate agents be?

Sixty minutes is the working minimum if the session includes a live build. Shorter slots force the speaker to demonstrate instead of build, which produces interest without adoption. Half-day and full-day formats allow a second build, CRM configuration, and a compliance review step. A 45-minute slot can work if it’s limited to one workflow.

How do you measure ROI on an AI keynote?

Measure usage at day 30, not satisfaction on day one. Choose one observable metric before booking — the share of new listings with AI-assisted marketing, the share of new leads followed up within an hour, or the number of agents who used the saved prompt. Compare it to a baseline you pull the week before the event.

What should agents bring to an AI keynote?

Agents should bring a charged laptop or tablet, a logged-in and tested account on the AI tool the session uses, and one real active listing or real lead to work on. Hypothetical material produces hypothetical adoption. Send these requirements a week ahead, so the first 15 minutes aren’t lost to password resets.

Which AI tool should a brokerage AI keynote focus on?

Focus the live build on the tool most of the room already uses, then teach prompt structure that transfers to any tool. According to NAR’s 2025 Technology Survey, ChatGPT is the most-used AI tool among Realtors at 58%, followed by Gemini at 20% and Copilot at 15%. Removing setup friction matters more than picking the newest model.

How do you get skeptical agents to use AI after a keynote?

Give skeptical agents one task they already hate and show them it’s done in minutes on their own material. In my coaching, skepticism usually comes from vague promises, not the tools themselves. A single finished listing description or follow-up message they’d actually send does more than any statistic. Then pair them with the internal champion for the first 30 days.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com/keynote/

AI for Non-Technical Real Estate Agents: Where to Start

Written by Coach Emily on October 5, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

AI for non-technical real estate agents starts with a skill you already have: explaining a task clearly, like briefing a new assistant. You don’t need code, integrations, or ten tools. One chat app, your voice, and one weekly task are enough. This guide gives the five-step system, the first prompt, and the review step that protects your license.

Key Takeaways

Using AI well is a briefing skill, not a technical skill, and agents brief people all day.
Start with one task you already do every week, not with a list of tools.
Talk to the AI instead of typing, because voice removes the biggest barrier for non-technical agents.
Save the brief that works so you never explain yourself twice.
Nothing AI drafts goes public until you’ve checked the facts, the fair housing language, and your broker’s name.

What does “non-technical” actually mean with AI?

Using AI as a non-technical agent means working in a plain chat app like ChatGPT, Claude, or Gemini. You type or speak instructions in everyday language. There’s no code, no software integration, and no automation to build.

If you can text a client and brief a transaction coordinator, you have every skill the first 90 days require. The technical layer comes later, if it comes at all. That layer means connecting AI to your CRM and building automated workflows.

Why this matters for real estate agents

Most agents are stuck at one of two points, and neither one is a technology problem. According to NAR’s 2025 Technology Survey (September 2025), 32% of agents hadn’t used AI in their business at all. Only 17% reported a significantly positive impact, and 46% said AI had no noticeable impact.

Read those together. A third of the industry hasn’t started. Nearly half of the rest are using AI and getting nothing measurable from it. Both groups share one cause: they treated AI as a tech project instead of a delegation problem.

The same NAR release frames technology around what it protects: in NAR Deputy Chief Economist Jessica Lautz’s words, “the trusted relationship between the agent and client.” That’s the point of all of this. AI should buy back the hours you spend drafting so you can spend them with clients.

“Every agent who tells me they’re not technical has briefed a transaction coordinator, a stager, and a nervous first-time buyer in the same afternoon. That’s the whole skill. AI needs the same brief, written down once.”
— Emily Terrell, Tom Ferry Coach

How do non-technical agents start using AI? The 5-step system

Which task should you hand to AI first?

Pick one task you do every week that’s mostly writing and that you’d happily delegate. Strong first candidates include:

first drafts of listing descriptions
follow-up texts to leads who went quiet
recap emails after showings
weekly social captions
a monthly market note to your sphere

Use three filters. The task repeats weekly. You already know what a good version looks like. And it costs you at least 30 minutes a week. Don’t start with your hardest problem. Start with the one you’ll repeat often enough to get good at.

Should you type or talk to AI?

Talk. The fastest way past “I’m not technical” is to stop typing. ChatGPT Voice lets you speak your request and hear the answer in the mobile app or on the web. Talk it through the way you’d leave a voicemail for your assistant: the property, the client, the goal, and what you’d say if you had time to write it yourself.

OpenAI’s own documentation notes that ChatGPT can make mistakes and that important information should be checked. That’s why Step 5 exists. Set your voice up before you drive, never while the car is moving.

What do you actually say to AI?

Give it the same four-part brief you’d give a new assistant:

Who you are: your market and your role.
What you need: the task and its length.
Who it’s for: the reader.
What good looks like: paste an example you’ve written that you like.

The example matters most, because it teaches your voice faster than any description of your voice.

Here’s a first prompt you can copy:

I’m a real estate agent in San Antonio. Write a first draft of a listing description for the home below. The readers are move-up buyers comparing homes in this price range. Keep it under 150 words, use no exclamation points, and don’t describe who the home is “perfect for.” Match the tone of this description I wrote: [paste your best description]. Use only these property facts: [paste your MLS input].

Then keep the conversation going. “Shorter.” “Lead with the kitchen.” “Less formal.” Revising is part of using AI, not a sign it failed.

How do you stop re-explaining yourself every time?

Save the brief once it works. In Claude, a Project holds your uploaded documents and your instructions and applies them to every chat inside it. Projects are available on free accounts, which can create up to five. If you work in ChatGPT, use its saved-workspace equivalent. The principle is identical.

What goes into a saved setup:

three samples of your best writing
your market and specialties
your brokerage name exactly as it must appear
a short list of words you never use

That setup is the difference between re-explaining yourself for 20 minutes every time and getting a usable draft in one message.

What do you check before anything goes out?

Check three things on every draft before it reaches a client or a feed.

Property facts. Check every fact against the MLS input, not against the draft. AI will describe a feature that doesn’t exist with complete confidence.
Fair housing language. Remove phrasing that signals a preference about who should live in the home. NAR’s Fair Housing resources are the reference.
Broker identification. In Texas, TREC Rule 535.155 treats social posts and emails as advertising, and AI drafts almost never include your broker’s name.

For the state-by-state detail, read what actually risks your license with AI-generated content. This is general information, not legal advice. Confirm specifics with your broker or attorney.

How I use this in my own business

I close 70+ transactions a year in San Antonio in about five hours a week of active management. I’m not an engineer. I’m an agent with ADHD who built systems because I didn’t want to babysit my business.

The first AI workflow that stuck for me wasn’t clever. It was talking. After a showing, I open voice mode before I pull out of the driveway. I talk through what the buyers loved, what killed it for them, and the questions they asked. By the time I reach the car line at school, I have a follow-up text drafted and a note ready for my CRM.

That’s still how I start agents who tell me they’re not tech people: one task, spoken, saved, and reviewed. When I teach this live to a brokerage, the room builds it on its own listings, not on a demo property. The full session design is what AI training for real estate agents must cover.

Common mistakes

Starting with a tool list instead of a task. Five tools with no workflow produce nothing. One task with one tool produces a habit.
Asking one-line questions and judging AI by the answer. “Write a listing description” gets a generic copy. The four-part brief gets your copy.
Re-explaining yourself in every chat. If you’re typing your market and tone for the fifth time, save the brief.
Pasting sensitive client data into a consumer chat app. Financial details and personal identifiers stay out of general-purpose tools.
Publishing straight from the chat window. Every draft goes through the three-point review, every time.

Frequently Asked Questions

Do I need to be good with technology to use AI as a real estate agent?

No. Using AI as a real estate agent requires clear instructions, not technical skill. If you can text a client, brief a transaction coordinator, and describe a listing out loud, you can get useful output from ChatGPT or Claude. The technical layer, meaning CRM integrations and automations, is optional, and you’ll get real value long before you touch it.

What’s the easiest AI tool for a real estate agent to start with?

The easiest AI tool is a general chat app you can talk to. ChatGPT is the most common starting point, and NAR’s 2025 Technology Survey ranked it first among the AI tools agents use, at 58%. Claude is a strong choice for writing in your own voice. Pick one, use it on one weekly task for 30 days, and skip tool comparisons until then.

Can I use AI on my phone?

Yes, and for non-technical agents the phone is often the better place to start. ChatGPT’s Voice feature lets you speak your request and hear the answer in the mobile app or on the web. Talk through a showing, a listing, or a follow-up between appointments, then refine the draft at your desk. Set it up before you drive, not while you’re driving.

How long does it take to learn AI as a real estate agent?

The first useful draft takes one conversation. Consistent results take a few weeks of using the same brief on the same task and correcting the output each time. That repetition is where the learning happens: you’re refining your instructions, not learning software. Agents who switch to a new tool every week tend to stay at the beginning indefinitely.

What should I never put into an AI tool?

Never paste a client’s financial details, Social Security number, account information, or other sensitive personal data into a consumer AI chat app. Many platforms retain what you enter, so check a tool’s data settings before using it for client work. Property facts, your own writing samples, and anonymized situations like “a buyer relocating for work” are safe starting inputs.

Do I have to tell clients I used AI to write my marketing?

In most states, there’s no general requirement to disclose that AI drafted your listing copy or captions. What’s required is that the content is accurate, not misleading, and compliant with fair housing and advertising rules like TREC Rule 535.155 in Texas. Rules vary by state and change often, so confirm with your broker. This is general information, not legal advice.

Will AI replace real estate agents?

No. AI drafts; the agent decides, negotiates, and carries the license. What’s changing is the gap between agents who use AI to get hours back and agents who don’t. Those hours go into work AI can’t do: pricing conversations, negotiations, and the client relationships that produce referrals. AI isn’t replacing you. The agent who knows how to use it is.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

Batch Real Estate Video Content: A Month in One Afternoon

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

You can batch real estate video content for a full month in one four-hour afternoon by planning 12 videos, scripting them with AI, filming them back-to-back, and scheduling them in a single session. Twelve videos cover three posts a week. This guide gives the hour-by-hour run of the show, the scripting prompt, and the compliance check.

Key Takeaways

A month of video content is 12 strong videos, not 30, and that number is what makes one afternoon realistic.
Deciding what to say is the real bottleneck, so the first hour goes to planning and scripting before the camera turns on.
Your best video topics are already in your inbox: the questions clients texted and emailed you in the last 30 days.
Batch evergreen content only, and leave one open slot per week for anything time-sensitive.
Run a compliance pass before you schedule, because a video filmed today may publish weeks after the facts in it have changed.

What is batch real estate video content?

Batching real estate video content means producing a full cycle of videos in one dedicated session, instead of creating each video on the day it posts. You plan, script, film, edit, and schedule as separate stages, running every video through each stage together. The result is a content calendar that doesn’t depend on how your week goes.

Why this matters for real estate agents

Social media is where agents already spend their marketing effort, and it’s where their leads come from. According to NAR’s 2025 Technology Survey, 75% of Realtors use social media in their business, and it remained the top lead-generating technology at 39%, ahead of CRM at 23% (NAR REALTOR® Technology Report). The channel isn’t the problem. The daily decision about what to post, made fresh every morning between showings, is.

The stakes go beyond new leads. According to NAR’s 2026 Member Profile, the typical Realtor earned 28% of their business from past clients, up from 20% the year before (NAR, 2026 Member Profile). A steady feed is how past clients remember you when a neighbor asks for an agent. A feed that goes dark for three weeks during a busy closing month hands that referral to someone else.

The four-hour run of show

Here’s the thing nobody wants to tell you: you don’t need more content ideas. You need a fixed sequence that turns the ideas you already have into scheduled videos in one sitting.

“A month of content isn’t thirty videos. It’s twelve good ones, planned in an hour and filmed in one sitting. The agents who post consistently aren’t more creative than everyone else. They decided what to say before they turned the camera on.”
— Emily Terrell, Tom Ferry Coach

How do you plan 12 videos in 60 minutes?

Pull your topics from real client questions, then script all 12 with AI before you film anything.

Spend the first 15 minutes scrolling the last 30 days of your texts, emails, and CRM notes. Write down every question a buyer, seller, or past client asked you. Then sort them into four buckets of three videos each:

Market and neighborhood: what’s selling, where, and why
Process: the questions every client asks, like earnest money, inspections, or appraisal gaps
Proof: past-client stories and results, shared with permission
Behind the scenes: how you actually work, what your week looks like

Spend the next 30 minutes scripting. Paste your questions into Claude or ChatGPT with this prompt:

You’re my scriptwriter. I’m a real estate agent in [city/neighborhood].

Here are 12 questions my clients asked me this month: [paste questions].

For each one, write a 45-second video script with:

1. A one-sentence hook that states the answer or a surprising specific

2. Three short talking points in plain spoken language

3. One call to action: [your CTA]

Match the voice in this sample: [paste 150 words of your own writing or a video transcript].

Avoid real estate clichés like “dream home” or “nestled.”

Flag any line that states a price, home value, or market statistic so I can verify it.

Use the last 15 minutes to read every script out loud. If a line doesn’t sound like you, cut it. The AI drafts. You decide.

How do you film 12 videos in one sitting?

Set up once, film in three blocks of four, and don’t watch playback between takes.

Put your light source in front of you, your phone at eye level, and a mic on your collar. Check the first clip for audio and framing, then stop reviewing. Film four videos, swap your top, film four more, swap again, finish the last four. The outfit changes keep a month of posts from looking like one Tuesday.

With scripts written, each 30- to 60-second video takes two or three takes. Budget 60 to 75 minutes for all 12.

How do you edit the whole batch fast?

Run every video through the same template in one pass: trim all, caption all, export all.

This is its own system, and I break it down step by step in the batch editing workflow. The short version: build one editing template with your fonts, colors, and outro, let AI generate captions, proofread street and neighborhood names, and export vertical cuts for every video in the same session. Budget 60 minutes, or hand this hour to a VA with the template.

How do you schedule and compliance-check a month of content?

Map the 12 videos to a calendar, stagger the buckets, and check every video against your state’s advertising rules before it goes live.

Assign three videos per week and rotate buckets so no week is all market updates. Pick your platforms deliberately. According to NAR’s 2026 Member Profile, agents use Facebook (76%), Instagram (57%), LinkedIn (55%), YouTube (31%), and TikTok (16%) professionally (NAR, 2026 Member Profile). Choose the two where your clients actually spend time and schedule there. If TikTok is one of them, these TikTok content ideas for real estate agents will fill future batches.

Then run the compliance pass. Batching creates a specific risk: a video filmed today may be published three weeks from now. In Texas, TREC’s advertising rule explicitly includes social media, requires your name and your broker’s name in a readily noticeable location, and allows that information to sit on your profile page when it’s directly linked (22 Tex. Admin. Code § 535.155). The same rule treats an ad about a property as misleading if it runs 10 or more days after closing without the property’s current status, and it restricts statements about a property’s value. Before you schedule, check three things:

Your broker’s name is visible on the video or on your linked profile.
Any property-specific video that will be published 10+ days after that property closed states the current status.
Every price, value, or statistic the AI flagged has been verified.

This is general information, not legal advice. Advertising rules vary by state. Confirm your requirements with your broker.

Budget 45 minutes. Your afternoon is done.

Common mistakes

Planning 30 videos. A target you can’t sustain produces two strong weeks and a dark month. Twelve you’ll actually post beats thirty you won’t.
Improvising on camera. Unscripted filming turns a 75-minute block into three hours of retakes. Script first, every time.
Batching time-sensitive content. Rate commentary, “just listed” posts, and local news go stale before they publish. Keep them out of the batch and film them live in your open slot.
Editing between takes. Switching between filming and editing restarts your setup cost on every clip. Finish each stage completely before starting the next.
Skipping the compliance pass. The video was accurate the day you filmed it. The rule applies the day it is posted.

Frequently Asked Questions

How many videos do real estate agents need per month?

Twelve is enough for most agents. That’s three videos a week, which is the consistency floor that holds up during busy transaction months. Posting daily for two weeks and then disappearing does more damage than a steady three-a-week rhythm. Start at twelve, prove you can sustain it for a full quarter, then add volume if your schedule allows.

How long does it take to film 12 real estate videos?

About 60 to 75 minutes if every script is written before you start recording. Each 30- to 60-second video takes two or three takes, plus a short reset between clips. Filming isn’t what slows agents down. Deciding what to say is. Script first, and the camera time shrinks to roughly five minutes per finished video.

What should real estate agents film when batching content?

Film evergreen content: answers to the questions clients ask you every week, neighborhood breakdowns, process explanations, and past-client stories shared with permission. These stay accurate for the full month. Leave one open slot each week for time-sensitive content like new listings, rate changes, or local news, and film that separately on your phone in five minutes.

Can AI write my real estate video scripts?

Yes, AI can draft scripts, but the questions have to come from you. Feed Claude or ChatGPT the real questions from your texts and emails, your market, and your voice, and it will return hooks, talking points, and calls to action in minutes. Edit every script out loud before filming. If a line doesn’t sound like you, cut it.

Do batched real estate videos have to follow advertising rules?

Yes. In Texas, TREC’s advertising rule covers social media, so videos promoting your services need your name and your broker’s name, which can sit on your linked profile page. Videos about sold properties posted 10 or more days after closing must state the property’s current status. Other states have their own rules, so confirm with your broker.

Should I batch content if I hate being on camera?

Yes, batching makes it easier. You warm up once instead of twelve times, and your later takes will almost always beat your first. For content you don’t need to film yourself, such as market updates or FAQ answers, an AI avatar tool can fill gaps. Keep your real face on anything where a client is deciding whether to trust you.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

For real estate agents who want to implement this: Get the weekly real estate prompt library at weeklyrealestateprompts.com or follow @coachemilyterrell on Instagram for daily systems and AI breakdowns.

How Many Transactions Can a Real Estate Agent Handle?

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

A real estate agent can handle as many transactions as their face-to-face hours allow, and AI raises that ceiling by eliminating admin work, not by showing homes or negotiating repairs. NAR’s 2026 Member Profile puts the typical agent at nine sides a year. This guide covers the capacity formula, the AI stack, and where people take over.

Key Takeaways

Your transaction ceiling is set by the hours only you can work (showings, appointments, pricing conversations, negotiation), not by your tech stack.
AI raises capacity by pulling admin work off every deal, which frees selling hours, but it doesn’t shorten the face-to-face work itself.
NAR’s 2026 data shows four-person teams closing a median of 32 sides, roughly eight per person, so adding people without systems doesn’t multiply output.
In my coaching, the agents who scale past 50 closings pair AI with at least one person in the transaction pipeline who isn’t them.

What is real estate agent transaction capacity?

Transaction capacity is the number of closings an agent can manage in a year before service quality, response time, or their own schedule breaks down. It comes down to two numbers: how many hours the agent can spend on work only they can do, and how many of those hours each transaction consumes. Everything else, including AI, either protects those hours or wastes them.

Why this matters for real estate agents

According to NAR’s 2026 Member Profile (June 2026), the typical agent completed nine transaction sides in 2025. For the first time, the same report separated team data: teams averaged four members, and team-based brokerage specialists reported a median of 32 sides.

Do the division. That’s roughly eight sides per person, about what an individual agent produces. NAR Deputy Chief Economist Jessica Lautz framed team growth as part of how Realtors are adapting to a hard market. That’s true. But the per-person math shows that adding people increased headcount, not per-person output.

AI hasn’t closed that gap on its own either. According to NAR’s 2025 Technology Survey (September 2025), 46% of agents said AI had no noticeable impact on their business, and only 17% reported a significantly positive one.

Here’s the thing nobody wants to tell you: more people won’t raise your ceiling by themselves, and neither will more tools. Systems do. People and AI are only as effective as the system they plug into.

“AI doesn’t give you more hours with clients. It gives back the hours you were losing to paperwork, and what you do with those hours decides whether you close 20 deals or 50.”
— Emily Terrell, Tom Ferry Coach

How do you calculate how many transactions a real estate agent can handle?

Your real number comes from your own calendar, not an industry benchmark. Work through these four questions in order.

What work can only you do?

Start by listing every task on a transaction that requires you personally. For most agents, that means showings, listing appointments, pricing conversations, offer negotiation, inspection responses, and the handful of relationship moments where the client needs to hear from you directly.

Track the hours you spend on those tasks for 30 days across every active deal. Divide by the number of deals. That’s your face-to-face hours per transaction, and it’s the most important number in your business.

What can AI take off every transaction?

AI should take over any task that repeats on every deal and can be reviewed before it goes out. That includes MLS descriptions, the listing marketing suite, follow-up drafts, CMA summaries, client status updates, and social content for new listings.

The key word is every. A task that happens once a year isn’t worth building a workflow for. A task that happens 40 times a year is. If you’re starting from zero, automating MLS listing syndication is one of the fastest places to win back hours.

What needs a person who isn’t you?

Some work needs a human, just not you. A transaction coordinator owns accountability: chasing lenders, catching missing signatures, and flagging a deadline before it becomes a problem. AI can draft the reminder email. It can’t pick up the phone when the title company goes quiet.

Showings are the next constraint. Once your calendar is full of tours, a showing assistant or buyer’s agent is the only thing that adds capacity.

What’s the capacity formula?

Capacity = annual selling hours ÷ face-to-face hours per transaction.

Here’s an illustrative example. Say you work 2,000 hours a year and admin eats 900 of them. That leaves 1,100 selling hours. At 25 face-to-face hours per deal, your ceiling is 44 closings. Move 500 of those admin hours to AI and a coordinator, and the ceiling rises to 64, without adding a single hour to your week.

This is the actual how. AI doesn’t make the showing shorter. It gives you back the hours the paperwork was taking.

What does capacity look like at each stage?

These are the patterns I see across the agents I coach, not industry benchmarks:

Solo, no support: Quality usually starts slipping somewhere between 25 and 40 closings a year. The limit is admin load, not talent.
Solo with AI and a transaction coordinator: Roughly 50 to 60. AI handles repeatable content and drafts, the coordinator owns contract-to-close, and the agent’s calendar is almost entirely face-to-face work.
Beyond 60: The agent is now running a team, even a small one. The next hire covers showings or buyer consultations, and AI keeps that team smaller than it would otherwise need to be.

How I use this in my own business

I close 70+ transactions a year in San Antonio on roughly five hours a week of active management, and I want to be precise about what that sentence means: I don’t close 70 deals alone. AI is the reason that the team stays small.

My MLS descriptions come from a saved Claude prompt that writes in my voice with Fair Housing constraints built in. I edit the output for about thirty seconds. The listing marketing suite doesn’t live in a chat window. It moves straight into the templates my transaction coordinator already uses, which is why the system keeps running during weeks when I’m on a stage instead of at my desk.

What AI never took over: the listing appointments, the pricing conversations, the negotiations. Those hours went to people, and that’s by design. I coach the same structure at Tom Ferry International. Start with the hours only you can work, then build everything else around protecting them.

Common mistakes

Buying tools before measuring hours. If you don’t know your face-to-face hours per transaction, you can’t tell whether a tool raised your ceiling or just filled your week with new tabs.
Letting AI send client-facing messages without review. A wrong price or an invented square footage goes out at scale. Every generated property fact gets checked against the MLS record, and every listing description gets reviewed against NAR’s Fair Housing guidance. This is general information, not legal advice; consult your broker on specific listings.
Hiring before building systems. NAR’s team data shows the result: four people producing roughly what four individual agents would. Document the workflow first, then hand it to someone. The guide to what agents can safely automate around the MLS is a good starting audit.
Comparing your solo numbers to a team’s numbers. A 70-deal benchmark from a team with support staff isn’t a target for one agent working alone. Measure yourself against your own formula.
Measuring AI by output instead of hours returned. Ten captions in two minutes means nothing if they never leave the chat window. AI training for real estate agents only works when every workflow has a destination.

Frequently Asked Questions

How many transactions does the average real estate agent do a year?

The typical Realtor completed nine transaction sides in 2025, according to NAR’s 2026 Member Profile. Teams, which averaged four members, reported a median of 32 sides. The gap between individual and team output comes mostly from structure: support staff, delegated tasks, and systems that run whether or not the lead agent is at a desk.

Can AI replace a transaction coordinator?

Not fully. AI can draft status updates, build deadline checklists from a contract, and write client emails, but a transaction coordinator owns accountability: chasing lenders, catching missed signatures, and escalating problems before they cost you the closing. The strongest setup pairs the two. AI produces the drafts, and the coordinator decides what goes out and when.

How many transactions can a solo agent handle without an assistant?

In my coaching, most solo agents without support start losing quality somewhere between 25 and 40 closings a year. The limit isn’t talent. It’s the admin load: every transaction carries paperwork, follow-up, and marketing that compete with showings and appointments. AI raises that ceiling, but a transaction coordinator usually raises it further.

What tasks should real estate agents automate with AI first?

Start with the tasks that repeat on every transaction: MLS descriptions, listing marketing copy, follow-up drafts, and client status updates. They’re high-volume, low-risk, and easy to review before sending. Save contract interpretation and pricing advice for yourself. AI should draft; you decide, and every generated property fact gets checked against the MLS record.

Does AI help real estate agents close more deals?

Only when it’s wired into a system. According to NAR’s 2025 Technology Survey, 46% of agents said AI had no noticeable impact on their business, while 17% reported a significantly positive impact. The difference is usually where the output goes. A prompt that lives in a chat window saves minutes. A workflow that lands in your CRM saves hours.

When should a real estate agent hire help instead of adding more AI?

Hire when the work left on your plate is face-to-face and you’re turning away business. AI can’t attend a showing, sit at a listing appointment, or negotiate an inspection response. If those hours are full and leads are still coming in, the next hire is usually a showing assistant or buyer’s agent, not another software subscription.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

Why Isn’t AI Working for Your Real Estate Business?

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

AI isn’t working for most real estate agents because they’re using it as a search box instead of a system. NAR’s 2025 Technology Survey found 46% of agents reported no noticeable impact from AI, and the tool is rarely the cause. This guide covers the five failure points and the exact fix for each.

Key Takeaways

When AI isn’t working for real estate agents, the cause is almost always missing context, missing structure, or missing destination, not the tool.
A voice file is the fastest fix for generic output, because AI can’t sound like you if it has never read you.
Saved prompts beat clever prompts, because a workflow you rebuild every time is a workflow you’ll abandon.
Output that doesn’t land in your CRM, templates, or a teammate’s checklist doesn’t count as a system.
Adding more tools almost never fixes a missing workflow. Cutting to one and building inside it usually does.

What does it mean when AI “isn’t working”?

AI isn’t working when the output takes as long to fix as it would have taken to write, or when it saves time on tasks that don’t move your business. It’s also not working when you use it in bursts and then stop, or when nothing it produces survives past the chat window. Most agents experience all three at once and conclude the technology is overhyped. It isn’t. The setup is missing.

Why this matters for real estate agents

Adoption stopped being the problem a while ago. According to NAR’s 2025 Technology Survey (September 2025), 20% of agents use AI tools daily and another 22% use them weekly. In the same survey, only 17% reported a significantly positive impact on their business, 33% saw a moderately positive impact, and 46% said AI had no noticeable impact.

That gap costs money, not just time. The same NAR survey found 24% of agents spend more than $500 a month on tech tools. When agents pay for subscriptions that never become workflows, the tool line on the P&L grows while the hours stay the same.

NAR’s own researchers frame technology as a means, not the point.

“Technology continues to be a powerful force in real estate, driving efficiency.”
— Jessica Lautz, Deputy Chief Economist, National Association of REALTORS®

Efficiency only shows up when the tool is wired into how you already work.

“Nobody’s AI problem is actually AI. It’s that the output has nowhere to live. If a draft isn’t in your CRM, your templates, or your transaction coordinator’s checklist by Friday, you didn’t build a workflow. You had a conversation.”
— Emily Terrell, Tom Ferry Coach

What are the five reasons AI isn’t working for you?

Are you giving AI enough context to sound like you?

Generic input produces generic output, every time. When you type “write a listing description for a 4-bed in San Antonio,” the model has nothing to work with except the average of every listing description it has seen. That’s why it sounds like everyone else.

The fix is a voice file: 10 to 15 samples of your own writing, plus your market, your farm area, your ideal client, and a short list of words you never use. Store it where the tool reads it automatically, such as a Claude Project or a custom GPT. Anthropic’s own prompting guidance makes the same point: being specific about what you want improves results. Specific context is the difference between editing a draft and rewriting it.

Are you rebuilding the same prompt every time?

A prompt you retype from memory is a habit you’ll drop by week three. Most agents write a strong prompt once, get a great result, and never save it. Two weeks later they write a weaker version from scratch, get a weaker result, and decide AI is inconsistent.

The fix is prompt architecture, not a prompt list. Every saved prompt needs five parts: role, context, constraints, output format, and an example. Build one for each recurring task and store them where you’ll find them in 10 seconds. I break down the structure in AI Training for Real Estate Agents: What It Must Cover.

Where does the output go after you copy it?

Output with no destination evaporates. If your follow-up email lives in a chat window, it doesn’t get sent on day 3, day 7, and day 14. It gets sent once, if you remember.

Every AI workflow needs a named endpoint: a Follow Up Boss template, an action plan, a saved email sequence, or a checklist your transaction coordinator already uses. Before you build any prompt, answer one question: where does this land, and who touches it next? If you can’t answer that, you don’t have a workflow yet.

Did you automate a process that was already broken?

AI makes a broken process faster, not better. If your lead follow-up had no clear owner, no timeline, and no script before AI, it now has no owner, no timeline, and a lot more drafts.

Map the process on paper before you add a tool: who does what, in what order, by when. Then put AI into the one step that eats the most time. For most agents, that’s the first draft of written communication, not the decision-making around it.

Are you paying for more tools than you use?

Tool sprawl feels like progress and works like a tax. Agents stack a writing tool, a video tool, a social scheduler, and three chat subscriptions, then use each one for a week. Nothing gets deep enough to save real time.

Pull your last three credit card statements and list every AI and tech subscription. Cancel anything you haven’t opened in 30 days or that duplicates another tool. Keep one general AI tool and your CRM, and add tools only when a specific, working workflow needs one.

How I use this in my own business

I close 70+ transactions a year in San Antonio in roughly five hours a week of active management. AI touches almost every piece of marketing my team produces, and none of it lives in a chat window.

My listing marketing suite runs from one saved prompt that already knows my voice, my market, and my compliance requirements. The output moves straight into the templates my transaction coordinator uses, so it runs the same way in a week when I’m on a stage instead of at my desk. Every content prompt ends with the broker identification requirement and a fair housing constraint. Every piece gets a human review before it is published, which takes about ninety seconds per asset.

Common mistakes

Judging AI on one bad output. A weak first draft usually means weak context, not a weak tool. Fix the input before you give up on the category.
Switching tools when the output disappoints. A new tool with the same empty prompt gives you the same generic result with a different logo.
Publishing without a fact check. AI will invent a square footage or a school district and drop your broker’s name from every caption. I cover the license risk in AI Real Estate Compliance: What Actually Risks Your License.
Handing AI to a VA with no written prompts. Your assistant can’t reproduce a workflow that only exists in your head. Saved prompts make the work delegable.
Measuring by feel. “It seems faster” isn’t a number. Write down your hours on a task before you systematize it, or you’ll never know whether it worked.

Frequently Asked Questions

Why does ChatGPT sound generic when I write real estate content?

ChatGPT sounds generic because it has no information about you, so it defaults to the average of every real estate post it has seen. Give it a voice file: 10 to 15 samples of your own writing, your market, your farm area, and the phrases you never use. Store it in a custom GPT or Claude Project so every draft starts from your voice instead of zero.

Is ChatGPT or Claude better for real estate agents?

Neither wins across the board. The right tool is the one you’ll build a saved workflow inside. According to NAR’s 2025 Technology Survey, ChatGPT was the most-used AI tool among agents at 58%, followed by Gemini at 20%. I use both Claude and ChatGPT daily. Pick one, build your voice file and three saved prompts there, and switch only when a specific task demands it.

How long does it take for AI to save a real estate agent time?

Time savings show up on the first task you systematize, not the tenth tool you try. Pick one recurring task, such as listing descriptions, post-showing follow-up, or weekly social captions. Build one saved prompt for it and run it on every instance for 30 days. Then compare your hours against the baseline you wrote down. If you didn’t write one down, start there.

How do I know if AI is actually working in my business?

AI is working when you can point to hours recovered or a task that now runs without you. Track three numbers for 30 days: hours on the task before, hours after, and editing time per output. If editing takes longer than writing from scratch, the problem is context or prompt structure, not the tool.

Should I stop paying for AI tools that aren’t working?

Cancel any AI tool you haven’t opened in 30 days or that duplicates a job another tool already does. According to NAR’s 2025 Technology Survey, 24% of agents spend more than $500 a month on tech tools. More subscriptions don’t fix a missing workflow. Keep one general AI tool plus your CRM, and add tools only when a specific workflow needs them.

Can AI-generated real estate content get me in trouble?

Yes, if you publish it unchecked. AI can invent property facts, drift into language that creates fair housing exposure, and drop the broker identification Texas requires under TREC Rule 535.155. The license holder owns the output, not the tool. Build compliance constraints into the prompt and review every piece before it publishes. This is general information, not legal advice. Consult your broker or attorney.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com

AI Real Estate Ads and Fair Housing: Where Agents Get Burned

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. Real estate’s leading voice on AI, systems, and social media.

AI real estate ads create fair housing risk in three places: who the ad targets, who the platform delivers it to, and what the AI-written copy says. You don’t have to mean to discriminate to be liable. This post breaks down where agents get exposed and the six-step check to run before any ad goes live.

Key Takeaways

You’re responsible for who your ad reaches and who it excludes, not just for what it says.
The most common exposure comes from “neutral” filters that act as proxies for protected classes: zip codes, interests, and lookalike audiences.
AI copy tools default to buyer-lifestyle language, and that language can read as steering.
Federal AI advertising guidance was withdrawn, but the Fair Housing Act itself didn’t change.
A five-minute pre-launch check removes most of the risk.

Is it legal to use AI to write and target real estate ads?

Yes. Using AI isn’t the problem. What the AI produces and what you tell it to target can be.

Here’s the thing nobody wants to tell you: the Fair Housing Act doesn’t care how the ad was made. Section 804(c) prohibits housing ads that indicate a preference based on a protected class. If a model wrote the copy and a platform picked the audience, the ad still carries your name and your license number.

The protected classes under federal law are race, color, religion, sex, disability, familial status, and national origin. Texas mirrors these, and many cities add more. Check your local ordinance before assuming the federal list is the whole list.

Where AI ads create fair housing risk

Most agents picture discrimination as something deliberate. The exposure I see in practice is almost always accidental. It comes from stacking reasonable-sounding choices.

Proxy targeting

You’d never target by race or family status. But zip codes, interests like “parenting” or “church events,” and tight radius choices can stand in for protected classes. One filter is rarely the issue. Three stacked filters usually are, because each one narrows the audience further.

Lookalike audiences built from past clients

This is the one that surprises agents. If your closed-client list skews toward one demographic, a lookalike audience reproduces that skew at scale. The platform finds more people who resemble the people you’ve already served.

This is the exact mechanism regulators went after at Facebook. HUD charged Facebook with violations of the Fair Housing Act on March 28, 2019, and in the settlement that followed in June 2022, Meta agreed to retire the Special Ad Audience tool — a lookalike modeling product that delivered ads to users who “look like” the advertiser’s source audience. That settlement is why Meta now requires housing ads to run under its housing Special Ad Category, which limits targeting options. NMP

Algorithmic delivery skew

Even when you choose broad targeting, the platform’s delivery engine optimizes toward whoever engages. Your ad can end up in front of a narrow slice of people without you choosing that.

You’re less likely to be the main target for platform delivery on its own. But “the algorithm did it” won’t cover the choices you made upstream, like the audience you uploaded or the campaign type you picked to get around housing restrictions.

AI-written ad copy

This is the risk I’d take most seriously if you’re writing listing ads in ChatGPT or Claude. Out of the box, AI writes about the buyer, not the house. That’s where steering language shows up:

“Perfect for young families”
“Ideal for empty nesters”
“Walking distance to St. Mary’s”
“Exclusive, quiet neighborhood”
“Great for working professionals”

Each of these indicates who the home is “for,” and that’s the problem. Describe the property. Let the buyer decide whether it fits their life.

AI-generated lifestyle images

If every generated image of a family in the backyard shows the same demographic, the image signals a preferred buyer as clearly as words would. Few agents are watching this yet. That’s the reason to get ahead of it.

What changed at the federal level, and why it doesn’t protect you

In 2024, HUD released guidance addressing the applicability of the Fair Housing Act to advertising of housing opportunities through online platforms that use targeted ads, including a recommendation to avoid targeting options that directly describe or relate to FHA-protected characteristics, or that are effectively proxies for such protected characteristics — either alone or in combination. Consumer Financial Services Law MonitorConsumer Financial Services Law Monitor

That guidance is gone. The Federal Register withdrawal notice lists an effective date of withdrawal of September 17, 2025. According to the National Apartment Association, these pre-existing guidelines have not been replaced with alternatives, leaving it to the courts to interpret the standards that must be followed. federalregister National Apartment Association

The truth is that less guidance doesn’t make you safer. It means you have less clarity. The statute still stands. Private plaintiffs, fair housing organizations, and state agencies can still bring claims. As a National Mortgage Professional analysis put it, the federal pullback merely redistributes risk and doesn’t eliminate it. NMP

The withdrawn guidance is still a useful checklist. You can read HUD’s original 2024 announcement for context.

The six-step check before any AI ad goes live

It’s not the “what”. It’s the actual “how” to do it. Run this before every listing ad. It takes about five minutes.

Declare the ad as housing. On Meta, every ad promoting a specific property or real estate service runs under the housing Special Ad Category. Don’t run listing ads as “brand awareness” or “engagement” campaigns to unlock more targeting.
Kill the lookalikes. Don’t build lookalike audiences from past-client lists for listing ads. Use broad geography.
Fix the prompt, not just the output. Add this line to every listing prompt you’ve saved: “Describe the property, not the buyer. Don’t reference family status, age, religion, nationality, disability, or who the home is ‘perfect for.'”
Run the house-or-person test. Read each sentence of the copy. If it describes a person instead of the property, rewrite it.
Check the images. If you’re using AI-generated lifestyle images, make sure they don’t show a single type of buyer. Or skip people entirely and show the property.
Screenshot your settings. Save the targeting and campaign settings for every ad. If a complaint ever comes up, documentation showing you chose broad targeting is your best evidence.

Here’s the honest tradeoff: broad targeting will probably cost you more per lead than a tight, stacked audience. That’s the price of doing this right. In my experience, compliant listing ads that describe the house well still perform.

“AI will write you a listing ad in thirty seconds. It’ll also tell buyers who the house is ‘perfect for’ in the same thirty seconds. The fix is one line in your prompt, and most agents haven’t added it.”
— Emily Terrell, Tom Ferry Coach

Who needs to take this most seriously

Every agent running ads needs this. Four situations carry more risk:

Agents running their own Meta ads without brokerage review. You’re the advertiser of record, and there’s no second set of eyes.
Teams using lookalike audiences built from their CRM. Your past clients reflect your past referral network, and that network may not reflect your market.
Agents who pasted AI copy straight into listings last year. Go back and audit what’s still live.
Anyone advertising rentals. Rental ads draw more testing activity from fair housing organizations. [Likely — confirm with your brokerage compliance team before publishing this line.]

Common mistakes

Treating AI output as finished copy. It’s a first draft, and a fair housing review is part of the editing.
Assuming the platform keeps you compliant. Special Ad Category limits some targeting options. It doesn’t review your copy or your uploaded audiences for you.
Believing the guidance rollback changed the law. It didn’t.
Writing for your ideal client in ad copy. Your ideal client belongs in your marketing strategy, not in the listing description.
Skipping documentation. If you can’t show what you targeted, you can’t defend it.

Frequently Asked Questions

Can real estate agents use AI to write listing ads?

Yes. No law prohibits using AI to write listing ads. The Fair Housing Act applies to the finished ad, whoever or whatever wrote it. If an AI-generated copy indicates a preference based on a protected class, such as “perfect for young families,” the agent who ran the ad is responsible. Review every AI draft before it is published.

Is “perfect for families” a fair housing violation?

It can be. Familial status is a protected class under the Fair Housing Act, and phrases that suggest a home is meant for a particular type of household can indicate a preference. The safer approach is to describe features, such as “four bedrooms” or “fenced backyard,” and let buyers decide whether the home fits their lives.

Did HUD withdraw its AI advertising guidance?

Yes. HUD withdrew its 2024 guidance on applying the Fair Housing Act to digital platform advertising, effective September 17, 2025. The withdrawal removed the guidance document only. The Fair Housing Act still applies to housing ads, and private parties and state agencies can still bring claims.

Are lookalike audiences allowed for real estate ads?

Lookalike audiences built from past-client lists carry real fair housing risk because they can reproduce the demographics of your existing clients. Meta retired its original lookalike tool for housing ads as part of a 2022 settlement. For listing ads, broad geographic targeting is the safer choice.

Do I have to use Meta’s Special Ad Category for listing ads?

Yes. Meta requires ads for housing, including property listings and real estate services, to be declared under its housing Special Ad Category, which limits certain targeting options. Running listing ads under other campaign types to access more targeting puts both your ad account and your compliance at risk.

How do I make my AI prompts fair housing safe?

Add one instruction to every saved listing prompt: describe the property, not the buyer, and don’t reference family status, age, religion, nationality, disability, or who the home is “perfect for.” Then read the output and rewrite any sentence that describes a person instead of the property.

The actual takeaway

You don’t need to stop using AI for your ads. You need one line in your prompts, one test before you publish, and one screenshot after. That’s the whole system. I post the AI workflows I actually use in my business every week. Follow along on Instagram at @coachemilyterrell.

This post is general information, not legal advice. For questions about a specific ad or your local laws, talk to your brokerage’s compliance team or a fair housing attorney.

What Is a Realistic AI Adoption Timeline for a Brokerage?

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. 4 years coaching at Tom Ferry, 9 years prior as a client.

A realistic AI adoption timeline for a real estate brokerage is 6 to 12 months, with weekly use by 60 to 70 percent of agents as the six-month target. A 50-agent office should set policy first, train a champion cohort second, then roll out one workflow at a time. This guide maps each phase and the metric to track.

Key Takeaways

Full adoption doesn’t happen, so plan for 30 to 35 weekly users in a 50-agent office by month six.
A written AI policy comes before the first training session, not after the first compliance problem.
A champion cohort of 6 to 8 agents creates the proof that moves the rest of the office.
Roll out one workflow at a time, because teaching tools instead of workflows is where most offices stall.
Measure weekly active use rather than training attendance, and check it at day 45.

What is an AI adoption timeline for a real estate brokerage?

An AI adoption timeline is the phased sequence a brokerage follows to move agents from occasional experiments to repeatable, office-wide workflows. It covers governance, training, rollout, and measurement, in that order. The timeline ends when AI use is written into onboarding and office standards, not when the last training session wraps.

Why does the timeline matter for brokerage leaders?

Most offices don’t have an access problem. They have a conversion problem.

According to NAR’s 2025 Technology Survey (September 2025), 20% of Realtors use AI daily, 22% weekly, and 27% a few times a month, while 32% hadn’t used it in their business at all. The same survey found that only 17% reported a significantly positive impact on their business, and 46% said AI made no noticeable difference. Two out of three agents also agreed that their brokerage already provides all the tech tools they need.

Read those numbers together. The tools are in the building, and agents are opening them. What’s missing is a sequence that turns occasional use into a workflow that changes production.

The agents are telling leaders what they need. According to an RPR survey of 225 NAR members reported by HousingWire (February 2026), 63% of agents named output accuracy as their top AI concern and 49% named compliance or legal issues. When asked which training would help most, 69% chose short video tutorials, 57% chose hands-on workshops, and 56% chose use-case training tied to real tasks.

“Technology continues to be a powerful force in real estate, driving efficiency and marketing innovation.”
— Jessica Lautz, Deputy Chief Economist, National Association of Realtors

A timeline that starts with policy and ends with standards answers both of those concerns. Agents get training built on real tasks, and the office gets the accuracy and compliance review it needs.

What does a 12-month AI adoption plan look like for a 50-agent office?

Plan the rollout in five phases. Each phase has one job, and skipping a phase is the most common reason offices stall.

For planning purposes, assume your 50 agents split into about 8 early adopters, 25 persuadable agents, and 15 holdouts. That split is a coaching benchmark, not a survey figure. It keeps leadership from judging a working rollout against a 100 percent target it was never going to hit.

What happens in weeks 0–2?

Set the guardrails before anyone trains. NAR’s guidance on why every brokerage needs an AI use policy lays out the core steps. Audit how agents already use AI, assign one person to oversee it, publish a list of approved tools, train agents on the rules, and build a review process so nothing goes straight from prompt to publication.

Then narrow the scope. Pick two or three starting use cases: listing descriptions, lead follow-up messages, and social captions. These happen often, are easy to measure, and match where agents already say AI helps most.

In Texas, AI-generated marketing is still advertising under TREC Rule 535.155, and generated listing copy can carry Fair Housing exposure. Put both in the policy on day one. This is general information, not legal advice, so have your broker or attorney review your final policy.

What should the first 30 days focus on?

Train a champion cohort, not the whole office. Choose the 6 to 8 agents who are already curious and have them build real outputs from their own listings and leads.

Each champion should leave day 30 with one finished asset and a documented time saving. Those results become your proof. A persuadable agent moves when a peer they respect shows them a finished listing package. A slide from leadership rarely does that.

How do you roll AI out office-wide in days 30–90?

Roll out one workflow every two weeks, starting with the ones your champions have already proven. Run a 20-minute live build at the weekly sales meeting, keep a shared prompt library the whole office can reach, and pair each champion with two or three agents.

This phase is where most offices stall, because they teach tools instead of workflows. Showing agents ChatGPT doesn’t change anything on its own. Handing them the exact prompt for their Tuesday follow-up block does. For the session structure itself, including the live build, prompt architecture, and compliance segment, see my guide to AI training for real estate agents.

What changes in months 3–6?

Add the second layer only for agents who have built the first-layer habit. That layer includes CRM automation inside tools like Follow Up Boss, AI-assisted video, CMA narratives, and transaction coordination.

Tighten the review process at the same time, because these outputs reach clients more directly. Pricing and market analysis need the most scrutiny. If your office is moving into listing data, work through how to integrate AI with MLS systems before any agent pastes an export into a chatbot.

How do you lock in adoption in months 6–12?

Turn AI workflows into office standards. Build them into new-agent onboarding, review the prompt library every quarter, revisit the AI policy when tools change, and report usage at the sales meeting the same way you report production.

By month 12, a new agent shouldn’t experience AI as a separate program. It should simply be how the office writes listings, follows up, and markets.

How do you measure AI adoption in a brokerage?

Measure weekly active use: the number of agents who used an approved AI workflow in the last seven days. Attendance tells you who was curious. Weekly use tells you whose behavior changed.

Set a checkpoint at day 45. If weekly active use isn’t climbing by then, the fix is more accountability, not more content. Add champion pairs, shorten the weekly ask, and cut any workflow agents aren’t using.

“Don’t measure AI adoption by who showed up to training. Measure it by who used a saved workflow in the last seven days. In a 50-agent office, that number tells you by day 45 whether the rollout is working.”
— Emily Terrell, Tom Ferry Coach

Common mistakes

Training before the policy exists. Agents are already using AI. Without approved tools and review rules, the first training session can put client data into consumer tools you can’t control.

Launching to the whole office at once. Without a champion cohort there’s no internal proof, and the persuadable middle waits to see whether the initiative lasts.

Teaching tools instead of workflows. A tour of five platforms produces admiration, not adoption. One prompt tied to one weekly task produces behavior change.

Tracking attendance. A full training room at week two says nothing about week eight. Weekly active use is the number that predicts whether the rollout holds.

Pushing advanced workflows too early. CRM automation and client-facing AI in month one overwhelm the middle group and create compliance exposure before the review process is ready.

Frequently Asked Questions

How long does it take a brokerage to adopt AI?

Most brokerages need 6 to 12 months to make AI a working habit, not a novelty. The first 90 days install two or three core workflows, months three to six add CRM and video layers, and months six to 12 build AI into onboarding and standards. Offices that skip the policy and champion phases usually stall around week six.

What percentage of agents should be using AI after six months?

Target 60 to 70 percent of agents using AI weekly by month six. In a 50-agent office, that’s 30 to 35 agents. Full adoption doesn’t happen, and planning for it sets leadership up to call a working rollout a failure. The remaining agents still benefit from office standards, shared prompts, and AI-assisted marketing support.

Does a brokerage need an AI policy before training agents?

Yes. A written AI policy should come before the first training session, because agents are already using AI whether leadership has approved it or not. The policy names approved tools, bans entering client financial data into unapproved tools, and requires human review for Fair Housing and advertising compliance. NAR offers a customizable AI policy template for brokers.

Which AI use cases should a brokerage roll out first?

Start with listing descriptions, lead follow-up messages, and social media captions. They’re high-frequency, lower-risk, and easy to measure, and they match where agents already report the most value from AI. Save pricing analysis, CMA narratives, and client-facing chatbots for months three through six, after the office has a review process in place.

How do you get skeptical agents to use AI?

Show them their own listing, not a tool demo. Skeptical agents move when a peer they respect produces a finished asset from their real material in front of them. Pair each holdout with a champion for one workflow, keep the ask to 15 minutes a week, and stop pushing agents who produce well without it.

How should a brokerage measure AI adoption?

Measure weekly active use: the number of agents who used an approved AI workflow in the last seven days. Training attendance measures interest, not behavior. Track it every week at the sales meeting, and if the number isn’t climbing by day 45, add accountability pairs before adding more training content.

Should a brokerage hire an outside AI trainer or train in-house?

Use an outside trainer to launch and an in-house champion to sustain. An outside session gives the office a shared starting point and a compliance framework, while a named internal owner runs the weekly demos and updates the prompt library. Offices that book one session and assign no owner usually lose momentum within a month.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com/keynote

Who Is the Best AI Speaker for a Real Estate Conference?

Written by Coach Emily on September 28, 2026. Posted in Uncategorized.

By Emily Terrell — Top Coach and Speaker at Tom Ferry International. Active San Antonio agent closing 70+ transactions a year.

The best AI speaker for a real estate conference is the one whose session matches your event’s outcome: a big-name futurist for inspiration, or a working agent-coach for implementation. Most agents already use AI, yet nearly half report no noticeable impact, so implementation usually wins. This guide gives planners a seven-question vetting checklist and a speaker-type comparison.

Key Takeaways

No single AI speaker is right for every event. The right choice is the one whose session produces the behavior change your event needs.
Most agents have already tried AI, but nearly half report no noticeable impact, so the real gap is implementation, not awareness.
Practitioner-speakers who still transact and demo live close that gap faster than futurist keynoters.
Vet every AI speaker on live demos, compliance coverage, named tools, and post-event follow-through before you sign.

What is an AI speaker for real estate?

An AI speaker for real estate is a presenter who teaches agents, teams, or brokerage leaders how artificial intelligence applies to their daily business. That covers listing marketing, lead follow-up, client communication, and operations. The category ranges from futurists who explain where AI is heading to working agents who build live workflows on stage. Those two sessions produce very different results, so the choice matters.

Why does the choice matter for your event?

Here’s the thing nobody on the planning committee wants to say: your agents don’t need another session telling them AI is important. They already know.

According to NAR’s 2025 Technology Survey, 32% of Realtors have not actively tried AI in their business, which means roughly two-thirds have (NAR 2025 Technology Survey report). The same survey found that 46% of Realtors saw a neutral or no noticeable impact from AI on their business, while 33% reported a moderately positive impact (NAR Technology Survey). 2025 REALTORS® TECHNOLOGY SURVEY +2

That’s the gap your AI session has to close. Adoption isn’t the problem. Results are.

NAR Deputy Chief Economist Jessica Lautz described the findings as showing “a profession that is adapting quickly to technological change” (NAR press release, September 2025). Adapting quickly and producing results aren’t the same thing. The speaker you book decides which one your audience walks out with. National Association of REALTORS

Credibility matters too. According to NAR’s 2026 Member Profile, the typical individual Realtor completed nine transaction sides in 2025 (NAR, June 2026). A speaker teaching AI to that room should be able to show the workflow holding up at real volume, not just in a demo account. National Association of REALTORS

What are the three types of AI speakers for real estate events?

The futurist keynote

A futurist keynote explains where AI is taking the industry and why it matters now. This type fits opening general sessions, association annual meetings, and events where energy and a shared vision are the goal. The watch-out: agents leave inspired and without a single workflow they can run on Monday.

The technologist or proptech executive

A technologist speaks from the product side: data platforms, analytics, and where the tech stack is going. This type fits broker and leadership tracks, especially when the audience is evaluating vendors or setting technology policy. The watch-out: product bias, and tools priced for enterprises rather than individual agents.

The practitioner-coach

A practitioner-coach still sells real estate, coaches agents, and teaches AI inside the context of a working business. This type fits breakouts, brokerage training days, and any session where implementation is the goal. The watch-out: less name recognition than a celebrity keynoter, so verify stage experience through bureau listings and past events.

“An AI session succeeds when every agent leaves with one workflow running in their own business within seven days. If a speaker can’t show you that workflow live, on a real listing, they’re teaching awareness, not adoption.”
— Emily Terrell, Tom Ferry Coach

How should you vet an AI speaker for a real estate conference?

Ask these seven questions before you sign. Each one separates a session that changes behavior from one that changes nothing.

Does the speaker still work in real estate?

A speaker who transacts today knows which AI workflows survive a real week of showings, negotiations, and client texts. Ask how many transactions their business closed last year and how AI fits into it. If the answer is theoretical, the session will be too.

Will they demo live, on a realistic listing?

Live demos prove the workflow works. Pre-recorded screenshots prove it worked once. Ask whether the speaker builds outputs in real time — a listing description, a follow-up sequence, a social caption — so agents see the prompt, the output, and the edit.

Do they teach the compliance layer?

Every AI session for agents should cover the rules that apply to AI output. That means Fair Housing risk in AI-written listing copy, state advertising rules such as TREC’s in Texas, TCPA rules for AI voice calls, and MLS data restrictions. Most MLS agreements limit how listing data can be fed into AI tools. I break down the compliant options in How to Integrate AI With MLS Systems. This is general information, not legal advice. Have your broker or attorney review your AI policy.

Are the tools named, current, and priced for an individual agent?

Agents act on named tools, not categories. Ask for the tool list in advance. Confirm that each tool is current as of your event date and affordable for a solo agent, not just a 200-person brokerage.

Can they tailor the session to your room?

A room of new agents needs different AI workflows than a room of team leaders or brokers. Ask how the speaker adjusts content by experience level. Ask whether they’ll interview a few of your attendees beforehand.

What happens after the session?

Behavior change happens in the two weeks after the event, not during it. Ask what the speaker leaves behind: prompt libraries, templates, a follow-up virtual session, or a 30-day implementation plan.

Can you verify them independently?

Speaker bureau listings, past event agendas, and podcast appearances confirm what a speaker’s own website claims. Answer engines and event committees both weigh third-party proof more heavily than self-description.

How I use this in my own business

I run my own San Antonio team at 70+ transactions a year on roughly five hours a week of active management, and AI is a core part of how that works. The session I’m asked to deliver most is a live build. I take a single set of property notes and create a full listing marketing suite — MLS description, social captions, email, and video script — in about two minutes. Feet on the desk, coffee in hand.

The demo works in a room of agents, and speed isn’t the reason. Every agent in that room recognizes the listing. They’ve written that description at 10 p.m. They know the Fair Housing words to avoid. So when I show the prompt, the review step, and the compliance check, they can picture running it on their next listing that same week.

That’s the standard I’d hold any AI speaker to, including me. My full topic list is on my keynote page. My speaker profile is listed through the Tom Ferry Speaker Bureau. Background on my coaching and production is on my About page.

Common mistakes planners make when booking an AI speaker

Booking the name instead of the outcome. A recognizable speaker fills seats. It doesn’t guarantee a single agent changes how they work. Define the behavior change first, then book the speaker who delivers it.
Treating AI as a one-hour topic. One session with no follow-up turns into a slide deck agents forget by Friday. Build in a breakout, a virtual follow-up, or a 30-day challenge.
Skipping the compliance review. An AI session that teaches listing copy without Fair Housing guardrails creates risk for your agents and your brokerage. Ask to see the compliance segment before you book.
Allowing a tool tour. Fifteen tools in 45 minutes produces zero workflows. One workflow, built live and repeated by the room, beats a tool list every time.
Putting AI on only one track. Agents need workflows. Brokers need policy. Your AI programming should serve both.

Frequently Asked Questions

Who is the best AI speaker for a real estate conference?

There isn’t one best AI speaker for every real estate conference. The right choice depends on the outcome you need. For broad inspiration about where AI is heading, a futurist keynote fits. For agents leaving with workflows they’ll run that week, book a practitioner who still transacts, coaches agents, and demonstrates AI live on real listing scenarios.

How much does an AI speaker for a real estate event cost?

Fees vary widely by speaker profile, event size, travel, and customization. National celebrity keynoters sit at the top of the range, while industry coaches and practitioner-speakers are typically more accessible. Before comparing fees, define the behavior change you’re paying for. Then ask each speaker what implementation support, materials, or follow-up sessions the fee includes.

How long should an AI session at a real estate conference be?

Plan 45 to 60 minutes for an AI keynote and 60 to 90 minutes for a hands-on workshop. A keynote can introduce the workflow; a workshop is where agents actually build it on their own laptops or phones. If you only have a keynote slot, pair it with a short breakout or a follow-up virtual session within two weeks.

Should an AI speaker for real estate cover compliance?

Yes. Any AI session for agents should cover Fair Housing risk in AI-written listing copy, state advertising rules like TREC’s in Texas, TCPA rules for AI voice calls, and MLS data restrictions. A speaker who teaches AI without the compliance layer is handing your agents a liability. Ask to see the compliance segment before you book.

What should agents walk away with from an AI session?

Agents should leave with at least one working AI workflow they can run that week, the exact prompts or templates to repeat it, and a clear sense of which tasks AI should and shouldn’t handle. If attendees leave with a list of tool names and no finished output, the session delivered awareness, not adoption.

How far in advance should you book a real estate AI speaker?

Book three to six months ahead for brokerage events and six to twelve months ahead for major conferences, especially in spring and fall convention season. AI content changes quickly, so confirm the speaker will update the session for tools and rules current at the time of your event, not the time of booking.

Bring this to your team or event

Book Emily to speak at your next event:
Email: eterrell@yourcoach.com
Phone: (210) 400-9191
Web: coachemilyterrell.com