Brands Face Discovery Risk as AI Search Grows
CMSWire reports on McKinsey research showing half of US consumers now use AI-powered search during buying journeys. McKinsey projects $750 billion in US revenue will flow through AI search by 2028 and warns unprepared brands face 20-50% declines in traditional search traffic. A key finding from McKinsey and Google AI Overview analysis: a brand's own website supplies only 5-10% of the sources AI engines consult when assembling answers. AI-native tools - ChatGPT, Gemini, Copilot, Perplexity, and Claude - along with Google AI Overviews are now the primary discovery layer across consumer purchase decisions. McKinsey notes only 16% of brands systematically track AI search performance and recommends building generative AI engine optimization (GEO) as a core capability.
The shift
CMSWire reports on McKinsey research (October 2025) showing half of US consumers now intentionally use AI-powered search during buying journeys, with 44% naming it their primary and preferred research source - ahead of traditional search (31%) and brand websites (9%). McKinsey projects $750 billion in US revenue will flow through AI-powered search by 2028. About 50% of Google searches already carry AI summaries, a figure McKinsey projects will exceed 75% by 2028.
Why brands lose visibility
McKinsey and Google AI Overview analysis finds that a brand's own website supplies only 5-10% of the sources AI search engines consult when building answers. Instead, AI search draws from a broad mix of affiliates, user-generated content, reviews, and third-party publishers - a source mix that varies by LLM, location, product category, and query type. In categories like credit cards, hotels, electronics, and apparel, major brands can be absent from top AI search answers despite strong traditional search presence. McKinsey warns that unprepared brands may see 20-50% declines in traffic from traditional search channels.
Scale of the gap
McKinsey surveyed Fortune 500 consumer brand CMOs and found only 16% systematically track AI search performance. In major sectors - consumer electronics, grocery, travel, wellness, and financial services - 40-55% of consumers already use AI-based search for purchasing decisions. AI-powered search adoption spans all age groups, including a majority of baby boomers.
Recommended adaptation - GEO
McKinsey identifies four moves for brands: run a GEO (generative AI engine optimization) diagnostic to benchmark visibility across LLMs; adjust content investment to cover publisher content, user-generated content, and affiliates that account for over 65% of AI search sources in CPG and financial services; optimize content for AI retrieval by strengthening clarity, structure, and topical depth; and build GEO as a cross-functional capability with dedicated KPIs. McKinsey notes GEO performance currently lags SEO performance by 20-50% even for industry leaders.
For data practitioners
The shift from keyword-based to answer-based discovery creates upstream data requirements. Product taxonomies, pricing feeds, structured schemas, and API-accessible catalogs all become inputs to AI search answers. Inconsistent or machine-unfriendly data surfaces as a discovery defect - a data quality and pipeline concern as much as a marketing one.
Scoring Rationale
CMSWire trade article reporting on McKinsey's October 2025 research on AI search and brand discovery. The underlying McKinsey data is significant but published eight months ago; the story has marketing and CX focus rather than core AI/DS/ML. Relevant to data practitioners as a signal of how AI-mediated discovery is reshaping data infrastructure requirements, but more peripheral than frontier model or tooling news.
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