When someone asks ChatGPT “who is the best personal injury lawyer in Chicago,” the response isn’t a list of links. It’s a direct answer: one to three firm names, often with a brief explanation of why each was recommended. This is fundamentally different from Google, where you rank and hope for a click. In ChatGPT, you’re either in the answer or you don’t exist.
ChatGPT draws on several signals when deciding which firms to recommend. The first is its training data — everything published about your firm before the model’s knowledge cutoff. Firms with thin web presence at training time start behind. The second is live retrieval: ChatGPT can browse the web in real time, pulling from your website, legal directories, news coverage, and review platforms. The third is structured data — JSON-LD schema, FAQ markup, and llms.txt files that make your firm’s services machine-readable.
Research published in Harvard Business Review in March 2026 found that AI platforms favor firms with strong reviews, specific and authoritative published content, quality attorney profiles in legal directories, and dense geographic presence in the markets they claim to serve. The firms earning recommendations have built something ad spend alone cannot buy.
What You Can Do About It
The signals ChatGPT uses are measurable and improvable. Faneros scans ChatGPT (and 5 other AI platforms) with the exact prompts potential clients use, shows you who is being recommended instead of you, and generates 9 deploy-ready files that improve every signal AI platforms use to decide who to recommend. The technical files — robots.txt, llms.txt, JSON-LD schema, FAQ schema, XML sitemap, and meta tags — take effect as soon as AI crawlers re-index your site.