As generative AI becomes a primary discovery channel, businesses are increasingly asking a new question: How do AI platforms decide which brands to recommend? A new study from Custom Legal Marketing offers fresh insight into that issue, revealing significant differences in how leading AI platforms rank and recommend law firms. The research highlights why Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) are emerging as critical strategies alongside traditional SEO.

Custom Legal Marketing (CLM) has published its first public report examining how leading AI assistants recommend businesses, using data collected through its proprietary Sequoia AI marketing platform. The study analyzed recommendation behavior across ChatGPT, Anthropic's Claude, and Google AI Mode, revealing that the three platforms rarely recommend the same law firms for identical legal queries.

The findings provide one of the largest publicly available datasets exploring AI recommendation behavior and underscore how generative AI is reshaping digital visibility for businesses. While traditional SEO has long focused on search engine rankings, marketers are increasingly optimizing content for AI-generated responses, where citation patterns and recommendation logic differ substantially across platforms.

Using its Sequoia platform, CLM submitted 9,600 AI queries—including 3,200 identical prompts to each AI system—covering 100 major U.S. cities and 32 legal practice areas. The prompts mirrored the way consumers naturally search for legal services, allowing researchers to compare recommendation consistency across multiple AI engines.

The study generated 107,716 citations referencing 19,692 unique law firm websites, creating one of the industry's most comprehensive datasets on AI-generated legal recommendations.

One of the report's most notable findings is the limited agreement among AI platforms. Across the complete dataset, only 2.9% of law firms were recommended by all three AI systems. When researchers compared identical prompts, overlap between any two platforms ranged from 2.8% to 8.6%.

Agreement declined even further when examining the top recommendation. ChatGPT, Claude, and Google AI Mode identified the same leading law firm in only 0.9% of comparable searches, suggesting that businesses cannot rely on a single optimization strategy to achieve visibility across multiple AI ecosystems.

The report attributes much of this variation to differences in underlying information sources. Claude heavily referenced legal directories such as Avvo and Martindale, while Google AI Mode relied more frequently on Super Lawyers, Yelp, and Reddit. These differences indicate that each AI platform evaluates authority, trust, and relevance using distinct combinations of web sources rather than a shared index.

Variation also emerged across legal specialties. Corporate law produced the highest level of agreement between AI platforms, with 45.2% of recommendations overlapping. By contrast, estate planning recorded no three-way agreement, while probate and trust-related searches produced agreement rates below 4%.

The research arrives as enterprises across industries invest more heavily in Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO). Unlike traditional SEO, which primarily targets search engine rankings, AEO focuses on improving how organizations are cited, summarized, and recommended within AI-generated answers produced by large language models.

Industry analysts increasingly recognize this shift. According to Gartner, generative AI is fundamentally changing digital discovery by moving users from keyword-based search toward conversational interactions. Similarly, Forrester has identified AI-powered search experiences as an emerging priority for organizations seeking sustained digital visibility and customer engagement.

The findings also reinforce the growing importance of structured content, authoritative digital assets, and trusted third-party citations. Rather than depending solely on website optimization, organizations must increasingly consider how AI systems interpret external signals from industry directories, reviews, editorial publications, and community platforms.

For marketers beyond the legal industry, the implications extend well beyond law firm visibility. Enterprise brands operating across healthcare, finance, retail, manufacturing, and B2B technology face similar challenges as AI assistants become trusted sources of product recommendations and business information.

Technology leaders including Microsoft, Amazon, Adobe, and Salesforce continue integrating generative AI into enterprise search, customer engagement, and marketing platforms, further accelerating demand for AI-focused optimization strategies.

The CLM study highlights an important reality for enterprise marketers: visibility in AI-generated answers is becoming increasingly fragmented. Success in the AI search era will likely depend on optimizing content not only for traditional search engines but also for multiple generative AI ecosystems, each with its own ranking signals, citation preferences, and recommendation methodologies.

Market Landscape

Generative AI is rapidly transforming search from keyword-based discovery to conversational recommendations. Gartner predicts AI assistants will become an increasingly important entry point for digital information, while Forrester notes that businesses are expanding Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) strategies to improve AI visibility. Organizations are now optimizing for citations, authority signals, and structured content alongside conventional SEO.

Top Insights

• CLM's study found that ChatGPT, Claude, and Google AI Mode rarely recommend the same law firms, highlighting fragmented AI recommendation behavior.
• Researchers analyzed 9,600 AI queries and more than 107,000 citations, creating one of the largest public datasets on AI-powered legal search.
• Differences in source material—including legal directories, review sites, and community platforms—appear to influence AI recommendations significantly.
• The findings reinforce the growing importance of Answer Engine Optimization and Generative Engine Optimization alongside traditional SEO strategies.
• Enterprise organizations should optimize digital authority across multiple AI ecosystems rather than relying on a single search optimization approach.

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