Observed Signal · Sep 3, 2026 · Research Release · Source: https://martechseries.com/feed/ · Impact: 2/5 · Sentiment: Neutral
AI Engines Disagree by 2× on Which Brands to Recommend
Treyci, an AI visibility intelligence platform, released measurement data showing that major AI engines (ChatGPT, Perplexity, Gemini, Grok) sharply disagree on which brands to recommend in buying-intent queries. In one B2B software category, one engine referenced tracked brands in 81% of answers while another did so in only 43%, a nearly two-fold visibility gap. The study scored over 1,200 AI answers from 100 buying-intent questions per category, repeated three times per engine monthly. Key findings: AI answers are probabilistic (same prompt yields different vendor lists across sessions), engines cite third-party reviews and publications rather than vendor websites, and adoption is ahead of measurement—only 41% of 100 B2B SaaS companies published llms.txt files. Founder Keith Schilling emphasizes that brands must measure the distribution of answers across engines, not rely on single screenshots.
Highlights significant inconsistency in AI engine recommendations, affecting brand visibility and SEO/GEO strategies, but is a niche measurement report from a startup.
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Key Takeaways & Evidence Grounding
- Treyci analyzed over 1,200 scored AI answers from ChatGPT, Perplexity, Gemini, and Grok.
- In one B2B software category, one AI engine mentioned tracked brands in 81% of answers while another mentioned them in only 43%.
- AI answers are probabilistic; the same buying question returned different vendor lists across separate sessions.
- AI engines primarily cite third-party sources (review platforms, comparison articles) rather than company websites.
- Only 41% of 100 B2B SaaS companies published an llms.txt file for AI crawlers.
Connected Companies & Entities
1 Entity mapped“Keith Schilling, founder of Treyci and previously an AEO/GEO practitioner at PayPal....”
Ontology Mapping & Concepts
Related Market Signals & Shifts
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Boosting B2B Brand Visibility in Generative AI Responses
MarTech published an analysis using the GEO tool Brandi to measure how often B2B technology brands are cited in generative AI answers. The study tracked over 1,000 English-language prompts across 29 B2B brands and four AI engines (ChatGPT, Perplexity, Grok and Google AI Mode/Gemini). Key findings: many B2B suppliers have low AI visibility (only 21% of brands appeared in more than 25% of relevant AI answers; one-third appeared in under 5%), owned website content drives more citations than earned media, and multimedia and platform content (YouTube videos, LinkedIn long-form posts) materially affect citation rates. Wikipedia and Reddit proved less important for B2B citations. The author concludes B2B companies need data-driven GEO strategies that include owned content, video, and platform-specific content to improve presence in AI-generated responses.
B2B Brands Risk Obscurity on AI Platforms, Study Finds
SEMAI analyzed 25,540 URLs cited by ChatGPT, Google Gemini, and Perplexity over a 60-day period and found each AI platform cites materially different content types. Blogs (41–55%) and webpages (38–47%) together account for more than 90% of AI citations, but platforms diverge on niche sources: ChatGPT cites LinkedIn, Wikipedia, and academic/research-backed content more than Gemini or Perplexity; Perplexity emphasizes comparison and solution pages; Gemini favors brand-owned blog content and avoids community sources. SEMAI argues that optimizing for a single channel (e.g., Google) can leave B2B brands invisible to buyers who begin research on AI platforms. SEMAI’s visibility platform tracks ChatGPT, Perplexity, Gemini, and Claude and offers LLM search volume metrics, cluster classifications, and AI-generated content calendars; a free AI visibility audit is available on its site.
AI Answer Engines Challenge Brands
An Adweek article (published May 1, 2026) summarizes a fireside conversation at ADWEEK House Possible co-hosted with Brandwatch in which ADWEEK Editor in Chief Ryan Joe and Brandwatch VP Eric deLima Rubb discussed how AI answer engines (e.g., ChatGPT) are reshaping search and the customer journey. Rubb cited an approximate 26% year‑on‑year growth in search activity and warned that AI models are being trained on social evaluation behavior from platforms like Reddit and forums. He advised marketers to treat AI as a stakeholder — influencing what AI cites by contributing authentic content on social platforms, leveraging visually rich sites like Pinterest (which he called under-indexed today), and monitoring post‑content conversations such as YouTube comment threads. The piece notes current measurement limitations for AI citation behavior and recommends an omnichannel approach while brands experiment to influence AI-driven discovery. The article was created in partnership with Brandwatch.
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