Waymark Research | July 2026
The following scenario is illustrative but reflects the kinds of questions brokers increasingly hear from Texas homeowners.
It was close to midnight when Sandra opened her laptop and typed the question into ChatGPT.
"Do I have to pay a real estate agent 3% to sell my house in Texas?"
She was not ready to call anyone. She did not want a sales pitch. She wanted to understand, quietly and on her own terms, whether the commission she had paid on her last home sale eight years ago was something she could avoid this time. Within two minutes she had a detailed answer about the 2024 NAR settlement, buyer representation agreements, and flat fee MLS services. She had never heard of any of it before that night.
She did not call an agent the next morning. She spent three more evenings with ChatGPT before she spoke to anyone in the industry.
Sandra is not unusual. She is, increasingly, representative.
The New Seller Journey
The sequence a Texas homeowner follows before listing their home has changed in a measurable way. Where sellers once moved directly from decision to agent contact, many now spend days or weeks in a self-directed research phase before any professional conversation takes place.
| Before | Today |
|---|---|
| Call a real estate agent | Ask ChatGPT or Claude |
| Learn the process from the agent | Research on Google |
| Accept the commission structure | Watch YouTube and read articles |
| Sign the listing agreement | Compare all available options |
| Contact a broker or platform | |
| Agent controlled the information. Seller arrived uninformed. | Seller arrives already informed. Broker advises rather than educates. |
The significance of this shift extends beyond consumer convenience. When sellers arrive at a professional conversation already understanding the NAR settlement, the option period, and the difference between a flat fee MLS service and a guided platform, the professional relationship changes. It becomes advisory rather than educational. Brokers and platforms that recognize this shift and adapt to it are better positioned than those that still rely on information asymmetry as a source of value.
AI Is Becoming the First Stop
While comprehensive industry data measuring how many homeowners consult AI before contacting a real estate professional does not yet exist, search behavior, AI adoption trends, and firsthand observations from brokers suggest the pattern is accelerating. The signals are consistent enough to describe the direction even if the precise scale remains unmeasured.
For decades, the first phone call a homeowner made when considering a sale went to a real estate agent. The agent controlled the information: what the home was worth, what it would cost to sell, what the process looked like from listing to closing. That information asymmetry was structural, and it shaped the entire listing relationship before a contract was ever signed.
That dynamic is shifting. A growing number of homeowners are turning to AI tools, specifically ChatGPT, Claude, Gemini, and Perplexity, before making any calls. They are asking detailed questions about pricing methodology, commission structures, disclosure requirements, contract terms, and the mechanics of a home sale. They are arriving at their first professional conversation already informed, already skeptical, and already aware of options that did not exist in their mental model a year ago.
The reasons are straightforward. AI tools are available at any hour. They are free. They do not have a financial stake in the answer. They respond conversationally, without pressure, without a follow-up call, and without the implicit expectation that asking a question means you are ready to sign a listing agreement. For a homeowner who wants to understand before committing, that combination is difficult to replicate.
"People are doing more research before they ever talk to a professional than at any point I can remember," said one licensed Texas broker who has worked in the San Antonio market for more than a decade. "They come in knowing things. The NAR settlement. What a flat fee MLS is. What the option period means. Information that used to take a full first appointment to explain."
The trend mirrors a broader pattern in consumer behavior. Before booking a flight, most travelers have already compared airlines, checked multiple booking platforms, and read reviews. Before scheduling a doctor's appointment, patients often arrive having researched their symptoms, their options, and the medications they might be prescribed. Real estate, one of the last professional services where information asymmetry remained largely intact, appears to be following the same trajectory.
Evidence We Can Observe
Comprehensive data measuring how many homeowners consult AI before speaking with a real estate professional does not yet exist. What does exist is a consistent set of signals pointing in the same direction.
AI adoption is accelerating broadly. OpenAI reported that ChatGPT reached 100 million users within two months of its launch, faster than any consumer application in history. By 2026, AI assistants from OpenAI, Anthropic, and Google have become standard tools for millions of Americans researching major financial decisions. Home sales are among the highest-stakes financial decisions most people make.
Search behavior reflects the shift. Google Trends data shows sustained growth in searches for terms including "sell house without Realtor," "flat fee MLS," "NAR settlement," and "ChatGPT real estate" following the August 2024 settlement announcement. Consumer interest in alternatives to traditional listing relationships is measurable and growing.
Brokers report the change directly. Practitioners across Texas markets describe sellers arriving at first consultations already familiar with the NAR settlement, already aware of flat fee MLS services, and already asking specific questions about option periods, buyer representation agreements, and disclosure requirements. That shift in the informed baseline of a first conversation did not happen through traditional media coverage alone.
The publishing market signals consumer demand. Sell Your Home With AI, written by Waymark founder and licensed Texas broker Michael Marelli, is among the first books covering the complete Texas home selling process using AI tools written by a licensed practitioner. Its publication reflects the same consumer demand this article describes.
What Texas Homeowners Are Asking AI
The questions homeowners bring to AI tools before a home sale fall into predictable categories. They are, notably, the same questions that listing agents have traditionally spent the first appointment answering.
Pricing. "How do I find out what my house is worth without hiring an agent?" "What is a comparative market analysis and how do I read one?" "Why is Zillow's estimate so different from what my neighbor sold for?" Texas presents a specific challenge here: the state is a non-disclosure state, meaning sold prices are not recorded in public deed records. AI tools explain this clearly and describe the limitations it creates for sellers trying to research their own market.
Commission. "Do I have to pay a real estate agent to sell my house?" "What did the NAR settlement change for sellers?" "Can I sell on the MLS without paying 3%?" The 2024 NAR settlement, which ended the requirement that sellers offer a buyer's agent commission as a condition of MLS listing, generated significant consumer awareness. AI tools explain the settlement accurately and in plain language that most homeowners can follow.
MLS access. "Can a homeowner list on the MLS without a real estate agent?" "What is a flat fee MLS service?" "How do I get my house on Zillow?" The answer, that MLS access requires a licensed broker but does not require a traditional listing agent relationship, is one that most homeowners have never encountered before. AI explains it clearly.
Disclosures. "What do I have to disclose when selling a house in Texas?" "Do I have to tell buyers about the foundation repair I had done?" "What happens if I don't disclose something?" The Texas Seller's Disclosure Notice, governed by Texas Property Code Section 5.008, has 13 sections and over 100 individual items. AI can explain the form's structure and what it is asking. It is less reliable on the nuanced judgment calls about what a specific prior condition requires.
Negotiations and contracts. "What is an option period in Texas?" "Can I negotiate the buyer's inspection repairs?" "What does earnest money mean and where does it go?" Contract mechanics that listing agents explain routinely are now available to any homeowner who asks. The TREC One to Four Family Residential Contract, which governs most Texas home sales, runs 11 pages. AI can translate its terms into plain English in minutes.
Closing costs. "How much does it cost to sell a house in Texas?" "What does the seller pay at closing?" "How do I calculate my net proceeds?" These questions were once answered exclusively at the closing table or by an agent running numbers. AI provides reasonable estimates and explains each line item in a seller's net sheet.
What AI Gets Right
The capabilities AI tools bring to a home sale research process are genuine and, in some areas, superior to what a busy listing agent can consistently provide during an initial consultation.
AI excels at explaining terminology. The vocabulary of a real estate transaction, option fee, earnest money, title commitment, T-47 affidavit, proration, recording fee, becomes accessible when a homeowner can ask "what does this mean" without feeling embarrassed or rushed. The patience of an AI system is infinite in a way that a professional on a schedule is not.
It is effective at comparing options. The differences between a traditional listing agent, a flat fee MLS service, and an AI-guided platform with licensed broker support involve tradeoffs that vary by seller situation. AI can lay out those tradeoffs systematically, without a vested interest in which option the homeowner chooses.
It generates useful checklists and frameworks. Before you list your home in Texas, there are tasks that benefit from systematic organization: gathering the survey, ordering the resale certificate if the home is in an HOA, completing the disclosure, scheduling professional photography, and setting up the AI tools that will support the transaction. AI builds these checklists accurately.
It drafts effectively. Listing descriptions, responses to buyer inquiries, and initial repair response frameworks are tasks AI handles well. A homeowner can produce a professional-quality listing description in 20 minutes using a well-structured AI prompt, a task that previously required either an agent's involvement or significant writing experience.
It explains process sequencing. The order in which things happen in a Texas home sale, disclosure before listing, option period after contract execution, inspection during option period, financing contingency after option period expires, survey delivery before closing, title commitment within 20 days of contract execution, is something most first-time sellers have never encountered. AI explains the sequence clearly.
Where AI Falls Short
The picture is not uniformly optimistic. AI tools have meaningful limitations in a home sale context, and understanding them matters as much as understanding the capabilities.
Local pricing judgment remains beyond what AI can reliably provide. The difference between what a home is worth on paper and what a specific buyer will pay in a specific neighborhood in a specific week involves variables that current AI tools cannot fully account for. Buyer demand patterns, the inventory level in a hyperlocal submarket, the reputation of a particular school that just changed attendance zones, the trajectory of a commercial development two miles away. These are the inputs that experienced local brokers carry in their working knowledge. AI does not have them.
Disclosure interpretation requires judgment that AI cannot provide and should not attempt to provide. Whether a prior foundation repair requires disclosure, whether a past water intrusion event rises to the level of material fact, whether a noise source from a neighboring property constitutes a known defect, these determinations involve legal nuance that varies by situation. AI can explain the general framework. It cannot tell you whether your specific situation requires disclosure without creating liability for everyone involved.
Negotiation strategy is not reducible to information. Knowing what the contract says and knowing how to negotiate effectively within it are different skills. An experienced broker reads a buyer's behavior, a buyer's agent's communication patterns, and the signals embedded in how an offer was structured. That reading informs negotiation strategy in ways that AI, working from document text alone, cannot replicate.
Legal responsibility does not exist in an AI system. A licensed Texas real estate broker has a fiduciary duty to their client. They can be held accountable by the Texas Real Estate Commission. They carry errors and omissions insurance. An AI tool carries none of those obligations. When a transaction goes wrong in a way that has legal consequences, that accountability gap becomes significant.
Verification of real-time data is unreliable. AI tools have knowledge cutoffs and cannot consistently access current MLS data, current interest rates, current title company fees, or current HOA assessment information. A homeowner relying on AI for precise numbers in a live transaction will encounter inaccuracies.
Why the NAR Settlement Accelerated the Shift
The August 2024 NAR settlement did not create consumer interest in alternatives to traditional listing agents. That interest existed before. What the settlement did was make the conversation about commission negotiability unavoidable.
For decades, the listing commission was presented to sellers as a standard cost of sale, as fixed and expected as title insurance. The settlement's requirement that buyer's agent compensation be negotiated separately, rather than embedded in the seller's listing agreement, made the structure visible in a way it had not been before. When something that was invisible becomes visible, consumers examine it.
The examination, increasingly, involves AI. A seller who types "NAR settlement what changed" into ChatGPT receives a clear explanation of both rule changes, their implications for buyer representation agreements, and the options now available to sellers who want to structure their transaction costs differently. That explanation leads naturally to questions about flat fee MLS services, AI-guided platforms, and what a seller can realistically handle without a traditional listing agent.
The parallel to other industries is instructive. TurboTax did not eliminate the tax preparation industry. It restructured it. Consumers who previously used a professional for every tax filing began using software for straightforward returns and professionals for complex situations. The professionals who adapted focused on the complexity that software could not handle. Tax software now handles more than 60 percent of individual returns filed in the United States.
Online banking did not eliminate bank branches. It restructured them around the transactions that still required human judgment. Travel booking sites did not eliminate travel agents. They redirected travel agents toward complex itineraries, group travel, and situations where expertise still commanded a premium.
Real estate appears to be entering a similar restructuring. The analytical and administrative work of a listing transaction is increasingly accessible to informed sellers through AI tools. The judgment work, negotiation strategy, disclosure interpretation, fiduciary responsibility, local market expertise, retains its value.
Michael's Perspective
I have been a licensed Texas broker for 15 years. In the past two years I have watched the pre-conversation change in a way I did not anticipate.
Sellers used to arrive at a first appointment knowing very little about the process. They knew they wanted to sell their home and they knew they needed help. The conversation started there. Now sellers arrive having already asked ChatGPT about the NAR settlement. They have already looked up what a flat fee MLS service is. They have already calculated what a 3% commission costs on their specific home. They are not uninformed. They are pre-informed, and they are skeptical in a productive way.
AI is not replacing brokers. It is replacing confusion. And that is a good thing for everyone in the transaction. A seller who understands the option period before an offer arrives responds more rationally than one encountering the concept for the first time under deadline pressure. A seller who has completed a disclosure walkthrough with AI assistance before listing is less likely to miss something material. A seller who understands their net proceeds before they accept an offer negotiates from a clearer position.
What I have not seen AI replace is the moment when something goes wrong and someone needs to know what to do. That moment still belongs to a licensed professional. It probably always will.
The Emerging Model: AI Plus Licensed Oversight
A pattern is emerging among sellers who want to avoid a full listing commission without navigating a transaction entirely on their own. They are using AI for the analytical and administrative work while retaining licensed broker access for the moments that require professional judgment.
This model, which some in the industry are calling guided home selling, represents a middle position between the traditional full-service listing relationship and the bare-bones flat fee MLS service that provides an MLS listing and little else.
Platforms built around this model combine AI-powered tools for pricing research, disclosure guidance, offer review, and deadline tracking with licensed broker availability at critical decision points. The premise is that most of what a listing agent does in a routine transaction is analytical and processual, and that AI handles those tasks well. The remainder, the judgment calls that carry legal and financial consequences, benefits from professional oversight.
Waymark Real Estate, a licensed Texas brokerage founded by broker Michael Marelli, operates on this model. Aria, Waymark's AI system, handles pricing analysis, disclosure guidance, offer review, and deadline tracking. A licensed broker is available at five moments in the transaction where professional judgment matters most: before the listing goes live, on every offer, through the inspection, on appraisal gaps, and at closing. The cost is $699 on the Launch plan or $1,199 on the Manage plan, with no percentage commission at closing.
"The tools exist to handle most of what a listing transaction requires," Marelli said. "The question is whether sellers have access to them in a form that is actually useful, and whether there is a licensed professional available when the situation requires something that tools cannot provide."
The Road Ahead
The question facing the residential real estate industry is not whether AI will influence how homes are sold. That is already happening. The question is how quickly the industry adapts to a consumer who arrives at the transaction more informed than any previous generation of home sellers.
For sellers, the shift represents a genuine expansion of options. The information that once required a professional relationship to access is now available to anyone willing to spend an evening with a capable AI tool. The judgment that still requires a professional is more clearly defined than it has ever been.
For the industry, the shift requires a reconsideration of where professional value actually lies. The agents and brokers who will thrive in this environment are the ones who focus on what AI cannot do: read a transaction, advise on strategy, exercise fiduciary judgment, and be accountable when something goes wrong.
Sandra, the Texas homeowner who started with a midnight ChatGPT query, eventually listed her home. She used a licensed broker. But she chose one after conducting more research, asking better questions, and understanding her options more clearly than she had in any previous real estate transaction.
Like many modern sellers, she entered the process understanding her options and chose the level of professional help that matched her needs.
"I knew what I was getting into," she said. "That felt different."
About Waymark Research
Waymark Research is an editorial initiative by Waymark Real Estate dedicated to publishing original analysis on how artificial intelligence is changing residential real estate. Recurring reports are planned throughout the year. The first annual AI Home Selling Report is planned for 2027. Journalists and researchers may request data and supporting materials at waymarkre.com/press.
About the Author
Michael Marelli is a licensed Texas real estate broker with 15 years of experience, founder of Waymark Real Estate, and author of Sell Your Home With AI. He holds TREC License 639078 through Marelli Properties and operates across San Antonio, Houston, Austin, and Dallas-Fort Worth. He can be reached for press inquiries at waymarkre.com/press.
