Google says people now type much longer questions in AI search, and often search with pictures, video, or voice. The claim came from Shivani Mohan, Google's Vice President of Data Science and User Experience Research for Search, on the October 28, 2026 episode of the Ads Decoded podcast, where she said query length has increased three times and that one in every six searches is multimodal.
The podcast episode, titled How AI is changing Google Search behavior and what it means for advertisers, featured host Ginny Marvin, Google's Ads Product Liaison. Mohan's two headline numbers describe a shift in how people express intent: instead of two or three keywords, searchers increasingly write full questions, add constraints, and follow up in the same session.
Coverage of the episode also flagged an important qualification. Neither figure came with a market, a time period, or a baseline in the episode, and both match numbers Google published in May with narrower qualifiers attached. The May report put AI Mode queries at three times traditional length and US multimodal use at more than one in six, so the podcast numbers describe a narrower slice of searches than the episode alone suggests.
Longer queries carry more intent in a single request. A searcher who writes a full question reveals their budget, their use case, their location, and their deal-breakers, which gives content creators far more to answer than a two-word keyword ever did. Pages built around one short keyword will feel thin against pages that answer the whole question and its natural follow-ups.
The shift also weakens the old keyword-counting mindset. When queries are conversational, matching the exact phrase matters less than covering the topic completely, with clear headings, direct answers, and supporting detail. Content that reads like a helpful expert answering a real question will fit AI search better than content engineered around a single term.
One in six searches being multimodal means a large share of searchers now combine text with images, voice, or video. For SEOs, that raises the value of image optimisation, descriptive alt text, video content, and pages that work when the entry point is a photo rather than a typed query.
Local and shopping searches are the obvious beneficiaries. A photo of a product, a room, or a storefront can start a search that ends in a purchase, and the pages that win will be the ones with strong images, accurate structured data, and clear next steps. Treat every image on a key page as a potential search entry point, not decoration.
Marvin closed the episode by noting that ads in Google's AI search surfaces are matched to both the query and the content of the AI response, and pointed retailers to six optional product data fields. That dual matching means ad relevance depends on the answer itself, not just the words the user typed, which makes feed quality and landing-page relevance more important than ever.
For advertisers, the practical lesson is to feed Google complete, accurate product data and to make sure landing pages genuinely deliver what the AI answer promises. An ad that matches the query but disappoints on the landing page will waste the click and teach the system nothing good about the brand.
Longer, multimodal queries reward the same asset link builders have always wanted: a genuinely useful page that answers a real question completely. Such pages earn citations inside AI answers, which in turn drive the referral traffic and links that compound over time. Thin pages built for short keywords have nowhere to hide when the query itself is a paragraph.
Audit your top pages against the questions people actually ask in full sentences. If a page answers only the short version of the question, expand it: add the comparisons, the constraints, and the follow-up answers. That expansion is both an SEO improvement and a link-building asset, since it gives other writers something worth citing.
Sources: ppc.land, October 31, 2026, covering the Google Ads Decoded podcast episode of October 28, 2026.
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