Serhant’s AI Pitch Raises the Bar for Listing Agents

Ryan Serhant put artificial intelligence at the center of his advice to real estate agents at NAR NXT 2026 in New Orleans, arguing that technology should absorb administrative work while people concentrate on relationships, creativity and dealmaking.

His remarks, covered by Realtor.com News on November 6, were directed at agents trying to grow their businesses in an uncertain market. But they also give homeowners a useful way to judge listing agents. AI can make an agent faster. It does not automatically make that agent more accurate, more attentive or better at protecting a seller’s proceeds.

Serhant’s message shifts AI from novelty to daily workflow

Serhant described AI as a tool for producing work, not merely generating language. He pointed to possible uses involving negotiation support, homeownership information and the reduction of routine tasks. His business test was practical: Does the technology help agents complete more transactions and improve profitability?

That fits the larger theme of his career story. Serhant recalled joining roughly 3,000 agents at a 2010 open casting call for Million Dollar Listing. Television exposure made him widely recognizable, and he followed it with an aggressive social media presence designed to reach prospective clients where they were already spending time.

His point in 2026 is that AI may be the next major distribution and productivity shift. Agents who adopt it effectively could respond faster, prepare marketing materials more efficiently and spend less time on repetitive office work. Sellers should care about those gains, but they should also ask where the saved time goes. If automation only enables an agent to carry more listings, the homeowner may receive less personal attention rather than more.

Sellers should test the agent, not admire the software

An agent’s claim to use AI is not, by itself, a reason to sign a listing agreement. The more useful question is what the agent automates and what remains under direct human review. Drafting an initial property description is different from setting a list price. Organizing showing feedback is different from interpreting why qualified buyers are hesitating. Preparing negotiation scenarios is different from deciding whether a concession is worthwhile.

Before hiring an agent, sellers can ask for a plain explanation of the workflow. Who verifies the listing description, room details and property features? Who checks comparable sales selected by a system? Does the agent personally review online inquiries and showing comments? Will the agent be available for pricing changes and offer discussions, or will those interactions be routed through automated messages?

Sellers should also request the evidence behind the recommended price. A credible analysis should identify the relevant comparable properties, explain adjustments and distinguish closed sales from active competition. An AI-generated summary may help organize that information, but it cannot inspect a home, understand an unusual renovation or know why one nearby transaction included concessions unless reliable data captures those facts.

Marketing deserves similar scrutiny. Automated copy can sound polished while saying very little. The listing should accurately communicate the property’s condition, improvements, layout and practical advantages without inventing features or hiding material problems. Sellers should review every public-facing description, image caption and factual claim before publication.

Buyers’ AI use makes defensible pricing more important

Serhant also described a buyer withdrawing from a $50 million transaction after consulting ChatGPT about whether the property was overpriced. One luxury deal does not establish a marketwide rule, but the episode illustrates a growing issue: buyers can now obtain an instant second opinion before their agent has finished explaining the numbers.

Those answers may be incomplete, based on weak assumptions or disconnected from the property’s actual condition. They can still influence behavior. A buyer who receives a confident automated warning may demand a discount, delay a decision or leave the negotiation entirely.

For sellers, the answer is not to argue with a chatbot. It is to build a listing position that can withstand scrutiny. That means documenting significant improvements, understanding nearby competing listings and knowing which comparable sales genuinely resemble the home. If the asking price includes a premium, the agent should be able to explain the premium with specific property and market evidence.

This preparation also matters after an offer arrives. Buyers may use AI to review inspection findings, estimate repair costs or generate negotiation language. A seller needs an agent who can separate a reasonable concern from a generic automated objection. Human judgment is especially important when comparing a price reduction with a repair credit, evaluating financing risk or deciding whether stronger terms justify a lower headline price.

Efficiency matters only when the seller benefits

Serhant’s broader argument was that agents should focus on what they can control rather than trying to predict every market turn. Sellers can apply the same discipline. They cannot control mortgage rates, buyer sentiment or the technology a prospective buyer consults. They can control preparation, pricing support, disclosure quality, marketing accuracy and the choice of representation.

A productive AI-enabled agent should be able to deliver faster follow-up, clearer organization and more time for conversations that require judgment. The warning signs are equally straightforward: generic marketing, unexplained pricing, inaccurate details, automated responses to sensitive questions or an agent who cannot describe how client information is handled.

Homeowners should avoid entering private financial details, access information or sensitive documents into unfamiliar AI systems. They should ask their agent what tools are used, what information is uploaded and whether a person reviews the output. Confidentiality and accuracy do not become less important because a task is automated.

The useful standard is not whether an agent looks technologically advanced. It is whether the process leaves the seller better informed and better represented. AI can shorten the route from raw information to a draft recommendation. Responsibility for the final pricing, marketing and negotiation decisions still belongs with people.