Observed Signal · Jul 17, 2026 · Opinion / Strategy · Source: The Drum · Impact: 3/5 · Sentiment: Positive
Marketers' playbook for brand visibility in AI agents
Jon Williams responds to Mark Ritson’s warning by offering a practical playbook for brands to remain visible and recommended by generative AI agents. He argues that fame functions as training data for large language models: brands that surface frequently become the model’s named recommendations, while weaker brands may be ignored. Williams recommends measuring a "share of model" metric (brand mention rate, recommendation rate, prompt coverage, model-specific visibility, volatility), using tools such as Semrush AI Visibility Toolkit, Profound and Peec AI, and optimizing content for citations rather than just search position. He highlights that paid AI discovery products are emerging (Google AI Mode, Perplexity, ChatGPT/OpenAI) and stresses the value of third-party validation channels like Reddit, review sites and editorial coverage to shape AI recommendations.
Highlights actionable marketing strategy for an emerging AI recommendation channel (GEO), identifies measurement tools and names major platforms building paid AI discovery — relevant to marketers and MarTech/AdTech planning.
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Key Takeaways & Evidence Grounding
- Jon Williams published an opinion guide advising marketers on brand visibility in AI-driven recommendation systems.
- Williams recommends measuring a brand's "share of model" using metrics like brand mention rate, recommendation rate and model-specific visibility.
- Three tools named to measure AI visibility are Semrush AI Visibility Toolkit, Profound and Peec AI.
- The article states that Google (AI Mode), Perplexity and OpenAI (ChatGPT shopping/ads) are developing paid/commercial AI discovery and advertising products.
- A multi-institution study (Princeton, Georgia Tech, Allen Institute for AI and IIT Delhi) is cited as finding content changes can increase source visibility in generative-engine responses by up to 40%.
Connected Companies & Entities
10 Entities mapped“Profound: Monitors specific prompts in answer engines and tracks visibility score, share of voice and average position....”
“Peec AI: Measures competitive share of voice across AI engines....”
“Google AI Mode: Google is testing and expanding conversational ad formats within AI-powered Search, including Shopping ads and sponsored pla...”
“Perplexity: The answer engine has introduced sponsored and commercial formats while building shopping and product-discovery features into it...”
“ChatGPT: OpenAI has introduced shopping research, product discovery, instant checkout and advertising products....”
“It also helps explain why brands such as Unilever are investing more heavily in creator-led work....”
“Reddit: Community discussions can provide AI systems with language, experiences and associations related to a brand....”
“Review platforms: Google Reviews, Trustpilot, G2 and Tripadvisor can contribute useful third-party evidence, although the most influential p...”
“Review platforms: Google Reviews, Trustpilot, G2 and Tripadvisor can contribute useful third-party evidence, although the most influential p...”
“Review platforms: Google Reviews, Trustpilot, G2 and Tripadvisor can contribute useful third-party evidence, although the most influential p...”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
AI Agents Favor Established Brands, Threaten Weaker Ones
Mark Ritson argues that agentic AI and large language models are reinforcing, not eroding, brand advantages. Using an anecdote about the Claude assistant recommending familiar bitter‑spirit brands, Ritson outlines research and industry metrics showing that chatbots and agents tend to prefer well‑known products — a phenomenon framed as popularity bias or incumbent advantage. Because agents often provide a single recommendation or small set of answers, the author warns they amplify visibility for already salient brands while stripping unearned margin from me‑too or weak brands. Ritson revisits past predictions that perfect information would kill brands and contends those forecasts overlooked brands’ role as time‑saving shortcuts; agentic AI may deepen that dynamic and reshape how marketers think about visibility, discovery and share of demand.
Beloved Brands Risk Being Invisible to AI
Adweek reports that iconic consumer brands returning to their origin stories (e.g., Nike, Starbucks, Burberry) are seeing early business improvements, but a growing intermediary layer of AI risks making well-known brands invisible to algorithmic recommendations. Autonomous agents and LLM-driven assistants are increasingly discovering, evaluating and recommending products; the article cites a 4,700% year-over-year increase in generative-AI traffic to U.S. retail sites (July 2025), Bain findings that 80% of consumers rely on AI-written summaries for much of their searches, and a Gartner projection of a 25% decline in traditional search volume. Firms like Danone and Gentle Monster are testing how AI assistants represent their products and adjusting marketing/search campaigns accordingly; Gentle Monster reported a 39% uplift in ROAS after aligning Google Performance Max campaigns with model language. The piece warns brands that lack clear, documented narratives risk absence or misrepresentation in AI-driven consumer journeys.
Boost Your Brand's Visibility in AI Search Today!
In a recent AdExchanger Talks episode, Tracy Morrissey, SVP of Media & Performance at Innocean USA, explains how brands can gain visibility in AI-generated search. She warns that you cannot simply bid your way to the top of large-language models; success hinges on creating content that directly answers real questions and on understanding how prompts indicate user intent. Brands should publish information on trusted sources—Wikipedia, retailer sites, and a brand’s own site—and verify origins by tracing sources used by AI. The episode notes firms that measure how often brands appear in AI search results, including Profound, Bluefish, and Semrush; it also notes Semrush was acquired by Adobe for $1.9B a week after recording. Morrissey discusses AI tool fragmentation, the need for better orchestration, the enduring value of human guidance in media planning, and a personal note about how dog training influenced her leadership.
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