Buyers Are Using AI to Research Agents. Most Agents Aren't Visible.

Written by:

Steve Marcinuk

Date:

07 Jul 2026

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For most of the past decade, real estate agents looking to generate leads online had a fairly predictable playbook: build a presence on Zillow, run some Facebook ads, and hope referrals filled in the gaps. That model is losing effectiveness. As buyers and sellers increasingly turn to AI-powered tools like ChatGPT and Gemini before they ever speak to an agent, the way agents get discovered is changing in ways the industry is only beginning to confront.

The timing matters because AI search tools are no longer experimental; they’re mainstream. Consumers are using them to research neighborhoods, gauge pricing, and ask for agent recommendations before ever visiting a traditional real estate website. Agents who aren’t visible in those results are missing a growing share of potential clients without realizing it.

Ryan Darani, Co-Founder and Chief AI Strategist at FlyDragon, has spent the past several years watching this play out. With 12 years of SEO experience, he launched FlyDragon to address what he saw as a gap in how the marketing industry served real estate agents. Most SEO providers in real estate, he explains, are add-ons to website or CMS providers rather than dedicated search visibility specialists. “There wasn’t a real focus for real estate agents to benefit from true SEO,” he says.

The numbers behind that observation are striking. Before launching FlyDragon, Darani reviewed 15,000 real estate agents’ websites and found that roughly 86-87% generated zero clicks and no traffic. That analysis became the foundation for a service now operating across 135 markets in the US and Canada, working with 115 agents, solo practitioners, brokerages, and teams.

The Visibility Problem

Many agents pay for websites that look professional but generate no inbound leads. They lack content, lead-capture mechanisms, and the structural elements that make them visible to AI tools and traditional search engines. “A lot of agents pay a monthly fee for a website, and the website just looks great, but it’s not functional,” Darani says.

FlyDragon’s onboarding process starts with a cleanup phase to ensure an agent’s information is consistent across all platforms and directories that reference them. From there, the work shifts to building what the firm calls a semantic content network: a structured body of content designed to answer the questions buyers and sellers are actually typing into AI tools, up to the point where someone asks which agent they should work with in a given market.

The off-site component focuses on building authority through press features and both local and national news coverage. The full cycle typically runs 90 to 120 days before agents start seeing meaningful inbound activity.

A Case Study

To illustrate how the process works in practice, Darani points to a team in Middletown, New York. Brian and Tracy Koplicki had recognized that AI search was becoming important and had tried to handle it themselves. Still, they found the work too time-consuming and technically demanding to manage alongside their actual business.

FlyDragon rebuilt their content strategy from scratch, overhauled their website’s conversion mechanics, and secured press coverage in New York-area outlets. Within roughly four months, the team began appearing among the top agents in AI search results for their market. Seven days after that visibility appeared, they closed three to four listings, generating approximately $45,000 in gross commission income. Darani notes that all of FlyDragon’s case studies are publicly verifiable on their website, with the agents named.

It’s worth noting that FlyDragon is one company among a growing number of firms working on AI search visibility for professionals. What distinguishes its approach, according to Darani, is the combination of on-site content strategy, off-site press placement, and a focus specifically on how AI models – rather than traditional search engines alone – surface recommendations.

The Zillow Dependency Risk

Beyond AI visibility, Darani consistently sees agents over-reliant on a single lead source. Many of the agents he speaks with draw 80 to 90 percent of their business from Zillow, with the remaining 10 percent coming from referrals. That works until it doesn’t.

The concern isn’t that Zillow is disappearing, but that depending on any single platform creates real vulnerability. Zillow can adjust its pricing, change its conversion rules, or shift how it allocates leads, and agents who haven’t built visibility elsewhere have limited options when that happens. “The agents who continue to win are the agents who put themselves in far more places than just Zillow,” Darani says.

Skepticism Is Becoming Harder to Sustain

Not every agent arrives at FlyDragon ready to invest. Darani describes the incoming client base as roughly split between those who immediately recognize the opportunity and those who previous marketing vendors have burned.

But the usual skepticism about new marketing channels is harder to maintain when agents’ own clients have already adopted the technology. Buyers and sellers are using ChatGPT to gauge pricing, research markets, and form opinions before they ever contact an agent. That reality makes it difficult for agents to dismiss AI search as irrelevant. “It almost forces that skepticism out of agents, because they understand their clients are already using it,” Darani says.

Unlike previous marketing channels, this isn’t something agents can choose to ignore on their clients’ behalf. The clients are already arriving at conversations with AI-generated context in hand.

Where the Market Is Headed

Darani’s longer-range view is that the industry may be underestimating how quickly AI tools will become embedded in the transaction process itself. He points to moves already underway at major portals and suggests that by mid-2027, possibly earlier, the ecosystem around buying and selling homes could look meaningfully different. “Ads have started to integrate into these models, and I just don’t think that agents understand how quickly this is going to compound,” he says.

FlyDragon is preparing in concrete ways. The company is set to appear at the Tom Ferry Summit in August 2026, where it plans to formally introduce its AI visibility service to a broader professional audience. Around the same time, the firm is releasing what it describes as a real estate citation index, built from an analysis of the ranking factors that influence how AI models surface and recommend agents. The index is intended to show agents exactly which platforms and signals matter most for AI-driven visibility, including which websites they need to be featured on to improve their chances of being recommended.

For agents still weighing whether this trend warrants action, the pattern Darani has observed is familiar from earlier platform shifts: the agents showing up in AI search results today largely got there by starting before the channel became crowded. Once competitors fill the space, the cost and difficulty of gaining visibility rises sharply. Whether the specific timeline Darani projects proves accurate, the direction of travel – consumers using AI tools earlier and more often in the home search process – appears unlikely to reverse.

About the Expert: Ryan Darani is Co-Founder and Chief AI Strategist at FlyDragon, an AI search visibility firm for real estate agents, with 12 years of SEO experience. The company operates across 135 markets in the US and Canada, working with 115 agents, brokerages, and teams.

This article is based on information provided by the expert source cited above. It is intended for general informational purposes only and does not constitute legal, financial, or real estate advice. Readers should conduct their own research and consult qualified professionals before making any real estate or financial decisions.