Most PPC teams still build campaigns the same way: pull a keyword list, set match types, and organize ad groups around search terms. It\u2019s muscle memory.<\/p>
But Google\u2019s auction no longer works that way.<\/p>
Search now behaves more like a conversation than a lookup. In AI Mode, users ask follow-up questions and refine what they\u2019re trying to solve. AI Overviews reason through an answer first, then determine which ads support that answer.<\/p>
In Google Ads, the auction isn\u2019t triggered by a keyword anymore \u2013 it\u2019s triggered by inferred intent.<\/p>
If you\u2019re still structuring campaigns around exact and phrase match, you\u2019re planning for a system that no longer exists. The new foundation is intent: not the words people type, but the goals behind them.<\/p>
An intent-first approach gives you a more durable way to design campaigns, creative, and measurement as Google introduces new AI-driven formats.<\/p>
Keywords aren\u2019t dead, but they\u2019re no longer the blueprint.<\/p>
The mechanics under the hood have changed<\/h2>
Here\u2019s what\u2019s actually happening when someone searches now.<\/p>
Google\u2019s AI uses a technique called \u201cquery fan out,\u201d splitting a complex question into subtopics and running multiple concurrent searches to build a comprehensive response.<\/p>
The auction happens before<\/strong> the user even finishes typing.<\/p> And crucially, the AI infers commercial intent from purely informational queries.<\/p> For instance, someone asks, \u201cWhy is my pool green?\u201d<\/span> They\u2019re not shopping. They\u2019re troubleshooting.<\/p> But Google\u2019s reasoning layer detects a problem that products can solve and serves ads for pool-cleaning supplies alongside the explanation. While the user didn\u2019t search for a product, the AI knew they would need one.<\/p> This auction logic is fundamentally different from what we\u2019re accustomed to. It\u2019s not matching your keyword to the query. It\u2019s matching your offering to the user\u2019s inferred need state, based on conversational context.\u00a0<\/p> If your campaign structure still assumes people search in isolated, transactional moments, you\u2019re missing the journey entirely.<\/p> Dig deeper: How to build a modern Google Ads targeting strategy like a pro<\/em><\/strong><\/p> An intent-first strategy doesn\u2019t mean you stop doing keyword research. It means you stop treating keywords as the organizing principle.<\/p> Instead, you map campaigns to the why<\/strong> behind the search. <\/p> The same intent can surface through dozens of different queries, and the same query can reflect multiple intents depending on context. <\/p> \u201cBest CRM\u201d could mean either \u201cI need feature comparisons\u201d or \u201cI\u2019m ready to buy and want validation.\u201d Google\u2019s AI now reads that difference, and your campaign structure should, too.<\/p> This is more of a mental model shift than a tactical one. <\/p> You\u2019re still building keyword lists, but you\u2019re grouping them by intent state rather than match type. <\/p> You\u2019re still writing ad copy, but you\u2019re speaking to user goals instead of echoing search terms back at them.<\/p> <\/p> Get the newsletter search marketers rely on.<\/p> <\/p><\/div> <\/p><\/div> <\/div> <\/p> Once campaigns are organized around intent instead of keywords, the downstream implications show up quickly \u2013 in eligibility, landing pages, and how the system learns.<\/p> If you want to show up inside AI Overviews or AI Mode, you need broad match keywords, Performance Max, or the newer AI Max for Search campaigns. <\/p> Exact and phrase match still work for brand defense and high-visibility placements above the AI summaries, but they won\u2019t get you into the conversational layer where exploration happens.<\/p> It\u2019s not enough to list product features anymore. If your page explains why<\/strong> and how<\/strong> someone should use your product (not just what<\/strong> it is), you\u2019re more likely to win the auction. <\/p> Google\u2019s reasoning layer rewards contextual alignment. If the AI built an answer about solving a problem, and your page directly addresses that problem, you\u2019re in.<\/p> The algorithm prioritizes rich metadata, multiple high-quality images, and optimized shopping feeds with every relevant attribute filled in. <\/p> Using Customer Match lists to feed the system first-party data teaches the AI which user segments represent the highest value.<\/p> That training affects how aggressively it bids for similar users.<\/p> Dig deeper: In Google Ads automation, everything is a signal in 2026<\/em><\/strong><\/p> Even as intent-first campaigns unlock new reach, there are still blind spots in reporting, budget constraints, and performance expectations you need to plan around.<\/p> Google doesn\u2019t provide visibility into how ads perform specifically in AI Mode versus traditional search. <\/p> You\u2019re monitoring overall cost-per-conversion and hoping high-funnel clicks convert downstream, but you can\u2019t isolate which placements are actually driving results.<\/p> AI-powered campaigns like Performance Max and AI Max need meaningful conversion volume to scale effectively, often 30 conversions in 30 days at a minimum. <\/p> Smaller advertisers with limited budgets or longer sales cycles face what some call a \u201cscissors gap,\u201d in which they lack the data needed to train algorithms and compete in automated auctions.<\/p> AI Mode attracts exploratory, high-funnel behavior. Conversion rates won\u2019t match bottom-of-the-funnel branded searches. That\u2019s expected if you\u2019re planning for it. <\/p> It becomes a problem when you\u2019re chasing immediate ROAS without adjusting how you define success for these placements.<\/p> Dig deeper: Outsmarting Google Ads: Insider strategies to navigate changes like a pro<\/em><\/strong><\/p> You don\u2019t need to rebuild everything overnight.<\/p> Pick one campaign where you suspect intent is more complex than the keywords suggest. Map it to user goal states instead of search term buckets. <\/p> Test broad match in a limited way. Rewrite one landing page to answer the \u201cwhy\u201d instead of just listing specs.<\/p> The shift to intent-first is not a tactic \u2013 it\u2019s a lens. And it\u2019s the most durable way to plan as Google keeps introducing new AI-driven formats.<\/p> <\/div> Contributing authors are invited to create content for Search Engine Land and are chosen for their expertise and contribution to the search community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. Search Engine Land is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.<\/em> <\/p> Opinion#Google #Ads #longer #runs #keywords #runs #intent1770379106<\/p> ","protected":false},"excerpt":{"rendered":" Most PPC teams still build campaigns the same way: pull a keyword list, set match types, and organize ad groups around search terms. It\u2019s muscle memory. But Google\u2019s auction no longer works that way. Search now behaves more like a conversation than a lookup. In AI Mode, users ask follow-up questions and refine what they\u2019re […]<\/p>\n","protected":false},"author":1,"featured_media":2959,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[152,75,670,9431,992,155,9430],"class_list":["post-2958","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-careers","tag-ads","tag-google","tag-intent","tag-keywords","tag-longer","tag-opinion","tag-runs"],"acf":[],"_links":{"self":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/2958","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2958"}],"version-history":[{"count":0,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/2958\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/media\/2959"}],"wp:attachment":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2958"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2958"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2958"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"Anatomy](\"https:\/\/searchengineland.com\/wp-content\/seloads\/2026\/02\/Anatomy-of-a-Google-AI-search-query.png\" "\\"Google")
<\/figure> <\/div> What \u2018intent-first\u2019 actually means<\/h2>
What changes in practice<\/h2>
Campaign eligibility <\/h3>
Landing page evolution<\/h3>
Asset volume and training data<\/h3>
The gaps worth knowing about<\/h2>
No reporting segmentation<\/h3>
The budget barrier<\/h3>
Funnel position matters<\/h3>
Where to start<\/h2>