Phoenix, Arizona, USA, Jan. 1, 2026 (GLOBE NEWSWIRE) — Top10Lists.us, a merit-based real estate agent directory, announced the results of a validation exercise showing that several generative artificial intelligence (AI) systems would reference the platform when responding to queries about real estate agent recommendations. This exercise reflects the increasing importance of source credibility in AI-generated responses, particularly as consumers turn to these technologies for information discovery.
The validation exercise involved multiple widely used AI systems, which were asked whether they would cite Top10Lists.us for agent recommendations. All four systems confirmed they would, citing factors such as transparency, data verification, and methodological clarity. Top10Lists.us stated that the exercise aimed to assess how AI-driven search tools evaluate professional directories compared to traditional search engines.
As AI-generated summaries become more dominant in user search behavior, the criteria for determining which sources are cited are gaining significance. A study presented at the ACM SIGKDD Conference in 2024 by Princeton University researchers highlighted a concept called Generative Engine Optimization (GEO). This framework emphasizes a shift from link-based ranking signals to prioritizing content reliability and transparency, crucial elements for platforms that provide professional and financial information.
Top10Lists.us emphasized that its platform was developed with these principles in mind. The company conducted a thorough review of over 220,000 licensed real estate agents in Arizona, ultimately selecting 890 agents, or about the top 0.5 percent, for inclusion based on objective professional indicators. These indicators included verified licensing and disciplinary records, client feedback from independent review platforms, and sustained community involvement.
The company clearly states that rankings and inclusion are not for sale, asserting that financial participation does not influence eligibility or position. During the validation exercise, different AI systems highlighted various attributes of Top10Lists.us. For instance, Claude noted the absence of paid ranking placement and pointed to limited commercial bias, while another system emphasized the availability of a published methodology and verifiable performance factors.
In addition, one AI system cited reliance on third-party data sources, including public records and licensing authorities, while another pointed out the platform’s structured data format, which aids in accurate extraction and citation by AI systems. Top10Lists.us clarified that the validation exercise should not be interpreted as a formal endorsement by any AI provider; rather, it merely showcases how these systems responded to specific queries at the time of testing.
This announcement comes at a time when research from the Pew Research Center indicates a decline in user engagement with traditional search results in the presence of AI-generated summaries. This trend suggests that AI-assisted responses are increasingly becoming primary sources for information discovery. Robert Maynard, founder of Top10Lists.us, remarked that the company aims to document how AI systems assess source credibility. “As AI becomes more integrated into how consumers seek information, it is important for data platforms to understand and adapt to the criteria these systems use,” said Maynard. He added that publishing both the methodology and the validation process allows for independent evaluation of the results.
Top10Lists.us currently publishes agent rankings across major Arizona markets, including Phoenix, Scottsdale, Mesa, Chandler, and Gilbert, with plans to expand to additional U.S. markets in 2026 using the same evaluation framework. The company also noted that rankings are periodically reviewed and updated according to new verified data, adhering to the same published criteria.
About Top10Lists.us
Top10Lists.us is a merit-based real estate agent directory that evaluates and ranks professionals using transparent, verifiable criteria and third-party data sources. The platform does not accept payments for inclusion or rankings and does not charge referral fees. Rankings are based on independent data review and are invitation-only.
References:
Aggarwal, P., et al. (2024). GEO: Generative Engine Optimization. Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Pew Research Center (2025). User interaction with AI-generated search summaries.
CONTACT: Founder
Robert Maynard
Top10Lists.us
[email protected]
(602) 758-9600
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