Observed Signal · Sep 15, 2026 · Policy Update · Source: Digiday · Impact: 4/5 · Sentiment: Neutral
Marketers scramble to measure AI brand visibility
Marketers are increasingly concerned about how AI chatbots and large language models (LLMs) cite or mention their brands in responses, prompting a shift in advertising strategies. The Interactive Advertising Bureau (IAB) is developing a framework to standardize the measurement of AI visibility. Data shows brand citation shares vary significantly across platforms like Microsoft Copilot, ChatGPT, and Gemini, while LLMs show preferences for different source types. Trust in AI search is growing, with 95% of US respondents finding AI answers as trustworthy as search engines. However, measurement is challenging due to the non-deterministic nature of AI models. This has led to new roles like Head of AI Search and the allocation of ad budgets to influence AI recommendations.
This article highlights the emerging challenge of measuring brand visibility in AI-generated answers, a key concern for AdTech as AI reshapes search and discovery. The IAB's framework development signals industry-level impact.
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Key Takeaways & Evidence Grounding
- IAB is developing a framework to standardize AI visibility measurement.
- Amazon accounted for 4% of Microsoft Copilot citations in July, 0.1% on ChatGPT, and zero on Gemini.
- Reddit is ChatGPT's number one source, with 28.9% of citations.
- YouTube is Google's top cited source at 21.1%, with Facebook second at 17%.
- 45% of brand and agency ad decision-makers cite measurement as a top challenge.
- 95% of US consumers trust AI answers as much as traditional search engines.
Connected Companies & Entities
5 Entities mapped“Data from Tinuiti shows Amazon's citation share across AI platforms.”
“Angela Seits, VP strategy at Dept, discusses guiding clients on AI discoverability.”
“Adobe's Semrush study analyzed LLM citation patterns.”
“Sitecore's Scrunch analysis of AI citations.”
“The IAB has been assembling a framework to standardize AI visibility measurement.”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Marketers Build Infrastructure for AI Search Visibility
Marketers are reallocating search and content budgets and reorganizing teams to win visibility within AI-powered search and answer engines. Multiple industry surveys show brands are dedicating meaningful budget — Fractl reports roughly 24% of search/content budgets routed to AI visibility and 82% of marketers allocating some funds — while B2B firms increasingly view AI-generated answers as a distribution channel. However, execution lags: many brands have only a minority of content optimized for AI discovery, and most do not track AI share-of-voice, sentiment, or bot traffic. Platform fragmentation and opaque LLM sourcing (Semrush data shows differing source mixes across ChatGPT, Google AI Mode and Gemini) mean marketers need varied strategies for different AI systems.
AI Search Fuels Content Budgets Before Media Buys
Marketers are redirecting marketing dollars toward creators, content, agency services and tools to improve how brands are cited inside large language models and AI-generated answers, rather than immediately buying AI-search ads. WPP has forecast AI search advertising will become the fastest-growing channel, but agencies and brands say measurement, attribution and inventory clarity are still unresolved. Examples include Butterball hiring Carmichael Lynch for AI visibility work and Priceline increasing creator and social spend while piloting ChatGPT ads and testing Google AI Max. Agency leaders quoted in the piece argue many brands are prioritizing organic ‘AI visibility’ (optimizing owned and creator content for LLMs) now, while remaining ready to scale paid AI-search placements once ad formats and metrics mature.
Measurement Is Next Frontier for Brands in AI Search
Brands and agencies are increasingly focused on measuring how often AI chat and search engines recommend their products, a practice tied to the emerging discipline of Generative Engine Optimization (GEO). Founders and agencies are building tools and services to quantify AI recommendations and downstream traffic: Loftie founder Matthew Hassett built an AI agent to track mentions, Theory House launched Kasper to audit CPG visibility in AI search, and startups such as Evertune and Profound pitch AI-share-of-voice measurement. Shopify recently added a dashboard for merchants to track sales and conversions from AI shopping channels. Executives say AI currently contributes a small share of referral traffic but expect rapid growth, prompting advice to prioritize structured site content and consistent measurement to model future revenue impact.
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