Key facts
- Real estate agents face a new challenge of gaining visibility and recommendations from AI platforms.
- Consumers are increasingly using AI tools like ChatGPT and Gemini for real estate insights.
- Agents need to ensure their online presence is understandable and recommendable by AI systems.
- A Realtor.com survey found 82% of U.S. adults interested in real estate used AI for insights in August 2025.
- Agents are advised to test their visibility on AI platforms and analyze competitors.
- A strong, branded website with relevant, localized information is crucial for AI recommendations.
Real estate agents are facing a new frontier in online visibility as consumers increasingly turn to artificial intelligence platforms for recommendations, shifting the focus from traditional search engine optimization to AI discoverability.
For years, agents have invested heavily in mastering Google search, optimizing websites, and collecting reviews to secure top spots in search results. Now, the challenge is to be identified and confidently recommended by AI systems such as ChatGPT, Gemini, and Perplexity. Shayan Hamidi, founder and CEO of Rechat, advises agents to reorient their strategies from solely focusing on SEO to ensuring they appear within AI-generated answers.
Mike Stensrud, founder of AgentEdgeAI, which helps agents improve their AI visibility, noted in his testing that prominent agents were surprisingly absent from AI recommendations in certain markets. This suggests that strong traditional search rankings do not guarantee AI recognition.
Consumer behavior is rapidly adapting, with a Realtor.com survey of 1,000 U.S. adults revealing that 82% were using AI for real estate insights in August 2025. ChatGPT was utilized by 67% of these respondents, and Gemini by 54%. The survey also indicated that consumers view real estate agents as highly accurate sources of housing market information, on par with AI, traditional media, and social platforms.
Hamidi likens the shift to how consumers have grown accustomed to recommendation engines on platforms like Amazon, suggesting that AI recommendations will become a natural part of the discovery process. He emphasizes that agents need to ensure AI systems have sufficient information to advocate for them.
Stensrud recommends that agents proactively test their own visibility by using prompts that potential clients might employ, such as searching for specialized agents in specific locales. He advises agents to analyze who is appearing on these AI lists and to ask AI for suggestions on how to improve their own standing. This process can reveal that strong Google rankings do not translate to AI recommendations.
To enhance AI discoverability, Hamidi suggests that agent websites should evolve beyond being mere digital business cards or listing portals. They need to provide valuable, specific, and localized information that directly addresses consumer queries. Stensrud adds that a strong, branded website that agents control is essential for showcasing expertise, blogs, reviews, and transaction history, serving as a central hub.
Consistency in name, address, and phone number across all online profiles, including websites, Google Business Profiles, and third-party platforms like Zillow, is critical for AI systems. This lack of fragmentation helps AI avoid confusion. Furthermore, third-party credibility, such as reviews, community references, and citations, plays a significant role in AI evaluations. Agents who consistently collect reviews and build recognition beyond their own websites are more likely to be recommended. A Spring 2026 study by withNotable identified Zillow reviews, Google Business profiles, and community forums as sources associated with AI recommendations, noting that specialty queries were more effective in generating specific agent names.