Google tells website owners nothing has changed for AI search

Google Search Relations team members John Mueller and Danny Sullivan told website creators on December 17, 2025, that optimizing for artificial intelligence-powered search requires no fundamental changes from traditional search engine optimization practices. The message directly contradicts months of industry claims that new acronyms like GEO, AEO, and LMEO represent distinct optimization disciplines requiring specialized strategies.

"Everything we do and all the things that we tailor and all the things that we try to improve, it's all about how do we reward content that human beings find satisfying," Sullivan stated during the Search Off the Record podcast episode. The former Google Search Liaison emphasized that ranking systems prioritize content written for people rather than algorithms or large language models.

The December 17 podcast arrives amid widespread confusion within the digital marketing community about whether AI-powered search features demand new optimization approaches. Sullivan acknowledged the natural reaction among professionals seeing format changes. "It's understandable. I think people really see stuff and they think they want to be doing something different," he said.

The guidance conflicts with prevailing industry narratives that have promoted AI search optimization as a distinct practice requiring specialized knowledge. Multiple terms have emerged throughout 2025 attempting to brand AI search optimization as fundamentally different from SEO, including Generative Engine Optimization, Answer Engine Optimization, and AI Optimization.

Sullivan expressed relief at not needing to track the proliferation of new acronyms. "My favorite thing is that we should be calling it LMEO because there's just so many acronyms for it," he said. "Is it GEO for generative engine optimization or AEO for answer engine optimization and AIO? I don't know. There's so many different names for it."

The Search Relations team published guidance in May 2025 after receiving repeated questions about what website owners should do differently for AI search. According to Sullivan, the team consulted with engineers before reaching a conclusion. "We came up with nothing really that different," he said. "That was kind of challenging."

The challenge stems from what Sullivan described as a "north star" principle underlying Google's ranking systems. All systems align toward rewarding content created primarily for human benefit rather than algorithmic manipulation. "The more you're trying to optimize or GEO or whatever you think it is for a specific kind of system, the more you're potentially going to get away from the main goal," Sullivan explained.

Traditional SEO tactics focused on gaming specific systems tend to fail as algorithms improve, according to Sullivan's assessment. Website creators pursuing temporary advantages through system-specific optimization often struggle when underlying systems evolve. "You went after one specific thing rather than going after the overall goal," he said.

The podcast discussion explicitly addressed only Google's systems. "We're only talking about Google, right? That's who we work for," Sullivan clarified. The guidance does not apply to other AI search platforms or conversational systems from competing technology companies.

Sullivan positioned AI-focused optimization terminology as a subset of SEO rather than a replacement discipline. "I think that one reframing of this is that you understand that there's these new formats and how do they apply into my world of SEO that I'm thinking about," he said. Local SEO and other specialized practices have existed within the broader SEO discipline for years without requiring entirely new frameworks.

The framing acknowledges that different content types may require specific considerations while maintaining connection to fundamental optimization principles. Sullivan compared the situation to local search optimization, which addresses specific listing requirements without divorcing itself from core SEO concepts.

Mueller contributed relatively brief comments during the December 17 discussion, primarily asking questions that allowed Sullivan to expand on Google's perspective. The Search Advocate role focuses on developer relations rather than public policy communication around search product changes.

Sullivan emphasized that many website creators do not need to think about SEO at all. "If you're not an SEO, you didn't do SEO, you don't think about SEO or you don't even know what that means, great," he said. "That's wonderful. You don't need to worry about this if your content is on the web and generally accessible."

The statement reflects Google's longstanding position that quality content naturally accessible on the web should perform well in search without manual optimization. Search Central documentation exists for those wanting technical understanding, but the company prefers creators focus on content quality rather than algorithmic considerations.

Sullivan noted positive reactions to this perspective from some content creators. "I've actually been heartened that I've seen a number of people saying things like, 'I don't even want to think about this SEO stuff anymore. I'm just getting back into the joy of writing blogs,'" he said. "That's what we want you to do. That's where we think you're going to find your most success."

The guidance creates complications for SEO professionals whose clients demand AI-specific optimization services. Sullivan acknowledged the challenge of telling clients that "the same old stuff" remains effective when competitive pressure exists to adopt new approaches. "I get you want the fancy new type of thing, but the history is that the fancy new type of thing doesn't always sort of stick around," he said.

SEO practitioners can position traditional best practices as the foundation for success with AI features, according to Sullivan's suggested approach. The emphasis remains on proven methods rather than experimental tactics targeting specific AI behaviors. "The best advice I can tell you when it comes to how we're going to be successful with our AEO is that we continue on doing the stuff that we've been doing," he said.

Mueller compared the current AI search transition to historical patterns where website creators attempted optimization for multiple search engines simultaneously. Before Google's dominance, some creators built separate versions of content for AltaVista, WebCrawler, and Open Text. "They would do six different versions of content for six different search engines," Mueller said.

Those multi-engine optimization strategies diminished as search engines converged toward similar quality evaluation approaches. The underlying systems aimed toward the same goals, making engine-specific tactics less valuable over time. Similar patterns may emerge with AI search optimization as systems mature.

Sullivan highlighted original content creation as the primary strength for website success in AI-powered search environments. Commodity content representing basic factual information becomes increasingly challenging to monetize as language models present that information directly. "More of this sort of commodity stuff, it isn't going to necessarily be your strength," Sullivan said.

The classic example involves annual searches for Super Bowl start times. Multiple websites traditionally created lengthy articles about game times, burying the actual answer within extensive background information. "And then at some point we could see enough information and we have data feeds and everything else that we just kind of said, 'The Super Bowl is going to be at 3:30,'" Sullivan explained.

Most users prefer direct answers for commodity questions rather than clicking through to website articles. "Thank you for telling me the time of the Super Bowl," Sullivan said, characterizing typical user reactions. Publishers previously competing for that traffic faced adjustment challenges, though the information lacked inherent originality.

Sullivan worried that some websites over-invest in commodity content optimization. Sites generating substantial traffic from daily word game answers exemplify the pattern. "That is great until the system shifts or whatever and it's common enough or we're pulling it from a feed or whatever and now it's like, 'Here's the answer,'" he said.

Original voice represents what only individual creators can provide. "Your original voice is that thing that only you can provide. It's your particular take," Sullivan emphasized. Content differentiation through unique perspective becomes more valuable as AI systems handle basic informational queries.

Authentic content creation extends beyond written formats. Sullivan highlighted video and podcast content as opportunities for firsthand perspectives. "People are also seeking original content that's authentic to them, which typically means it's a video, it's a podcast, because we're talking. See, now we're more authentic," he said.

Google has integrated more social and experiential content into search results, reflecting user demand for personal perspectives alongside expert analysis. "People want that sometimes, like you're just wanting to know someone's firsthand experience alongside some expert take on it as well," Sullivan said.

The multimodal aspect represents another area where AI search and traditional search align. Sullivan dislikes the term multimodal but acknowledged its technical accuracy. Users can search with one content type and receive results in another format. "I was walking around in Portland and I saw these geese on the ground," Sullivan recounted. "I did a video of them and then I sent it off to Google. 'What are they doing?' And it came back and it said, 'They're eating.'"

The system identified the activity from visual input and provided textual responses. Sullivan reported using this functionality extensively for various tasks. "I was clearing out my closets and getting rid of some stuff and I'm like just taking pictures of things. 'What is this worth?'" he said.

Content creators producing images and video alongside text potentially gain opportunities in multimodal search experiences. The recommendation applies beyond AI-specific features to traditional search results. "This isn't just AI specific. It's been one of these things that something that you could be thinking of," Sullivan said.

Structured data received brief mention as potentially helpful without representing a critical factor. "It wasn't like if you didn't have structured data, that's it. You're done for," Sullivan said. The team included structured data guidance because professionals do not always consider it, though it functions as one optimization element among many rather than a breakthrough tactic.

Success measurement represents the final major guidance area. Sullivan emphasized that website owners must define their own success metrics beyond simple click volume. "Sometimes, even in this age, people aren't seeming to even define what their success is beyond 'I got a lot of clicks,'" he said.

Quality clicks and quality conversions matter more than raw traffic numbers, according to Google's assessment. New AI formats appear to deliver more engaged visitors. "The one real thing that we've been finding with these new formats is that people arrive and they seem to be more engaged when they get there," Sullivan said.

Time on site provides a proxy metric for engagement quality. Google tracks visit duration to understand whether users find content satisfying after clicking through from AI-generated responses. "We can understand the time of visits or whatever and so we can understand they're spending more time on the sites," Sullivan explained.

Multiple industry studies have documented higher conversion rates from AI search traffic compared to traditional organic search visitors. Research published by Semrush in June 2025 found AI search visitors demonstrate 4.4 times higher value than conventional organic traffic when measured by conversion metrics.

Sullivan believes AI formats improve contextual awareness before users reach websites. Traditional search often requires multiple queries as users refine understanding of their own needs. "You do a search, you get some results back, maybe you click on something, you go, 'That's not really it.' You click back. You do another search," he said.

Query fan-out techniques allow AI systems to perform multiple related searches simultaneously. Mueller explained that the approach "does a whole bunch of searches for you" based on understanding user intent. The comprehensive information gathering happens before presenting results, potentially explaining improved engagement metrics.

The technical implementation creates situations where websites rank in traditional search results but not in AI-generated responses. Sullivan addressed this confusion directly. "The search is what the person searched for, but we went beyond that with the AIOs when all those incremental things," he said.

AI Mode users receive extensive contextual information bringing them closer to their actual information needs. "If you have been getting a lot of these incremental clicks and they've clicked away, maybe that was a visit, but maybe that wasn't really a good value to you," Sullivan suggested. "Whereas the people coming in who are converting better might be better prospects."

Conversion tracking requires website-specific implementation beyond Google's standard tools. Search Console cannot automatically measure conversions without integration with analytics platforms tracking user behavior beyond initial landing. "If you want to go into that deep, they're way beyond the kind of stuff I deal with," Sullivan acknowledged.

The underlying message emphasized measurement sophistication. "Measure your full value. That's what you're asking. How do I know if I'm successful? It's like, well, we don't know how you know if you're successful. Only you know that you know how you're successful," Sullivan said.

Sullivan compared current AI search evolution to historical search development. Before modern technology enabled natural language processing, users interacted with search engines through limited keyword inputs. He cited Brian Pinkerton's classic metaphor about someone walking into a library and saying only "travel" to a librarian.

"The librarian would turn to you and say, 'Well, okay, that's nice. Did you want to travel anywhere in particular? Are you interested in the history of travel? Are you wanting to go on a boat, on a plane, a train?'" Sullivan recounted. Search engines lacked conversational ability, forcing development of proxy signals for understanding intent.

Modern AI search enables the natural conversational search users probably wanted originally. "You can have these conversations. You can start off with the conversation where you can go in and say, 'I want to make a pizza. Can you tell me the kinds of stoves that would be useful for me to use if I want to do it in my backyard or garden or whatever?'" Sullivan explained.

The natural interaction pattern potentially benefits everyone involved. "If it re-energizes people to want to search, then hopefully everybody's being successful along the way," Sullivan said.

The guidance arrives as Google faces mounting criticism from publishers experiencing traffic declines following AI Overview expansion. Research analyzing 300,000 keywords found AI Overviews reduce organic clicks by 34.5% when present in search results, according to April 2025 analysis from Ahrefs.

Google executives including Nick Fox and Liz Reid have defended AI search features throughout 2025, maintaining that "the web is thriving" despite publisher concerns. The company emphasized quality over quantity in referral traffic, suggesting fewer but more valuable clicks represent positive outcomes.

Sullivan's December 17 message to website creators maintains consistency with previous Google statements. The fundamental advice remains unchanged: create quality content for human audiences, implement basic technical best practices, and measure outcomes based on business objectives rather than vanity metrics.

The podcast episode was recorded and published on December 17, 2025, appearing on Google Search Central's YouTube channel. The discussion represented part of the ongoing Search Off the Record series featuring conversations between Google Search team members about industry topics.

Timeline

May 2024: Google launches AI Overviews globally, beginning expansion across 100+ countries

May 2025: Google Search Relations team publishes blog post advising no changes needed for AI search optimization

May 20, 2025: Google expands AI Mode access to all United States users, eliminating previous waitlist restrictions

June 16, 2025: SEO consultant Aleyda Solis releases comprehensive AI Search Content Optimization Checklist

June 17, 2025: Google integrates AI Mode data into Search Console performance totals

June 25, 2025: Liz Reid discusses AI Mode advertising rollout and spam prevention measures

July 8, 2025: Brainlabs publishes analysis showing AI search requires multi-platform visibility strategies

July 16, 2025: SEO expert warns about potential "Zero Result SERP" scenario as AI Overviews reduce organic traffic

August 14, 2025: John Mueller warns against AI SEO acronym hype on Bluesky

October 27, 2025: CEO dismisses SEO professional believing AI makes traditional optimization obsolete, traffic drops 70%

December 11, 2025: Google launches December 2025 core update affecting ranking systems globally

December 15, 2025: Nick Fox tells publishers AI search requires same optimization as traditional search

December 17, 2025: John Mueller and Danny Sullivan publish Search Off the Record podcast explaining traditional SEO practices remain effective for AI search

Summary

Who: Danny Sullivan, Google Search Liaison, and John Mueller, Search Advocate at Google Switzerland, discussed SEO and AI search optimization on the Search Off the Record podcast. Sullivan previously spent 20 years writing about search before joining Google, while Mueller handles developer relations for the search team.

What: Google's Search Relations team stated that optimizing for AI-powered search features requires no fundamental changes from traditional SEO practices. The guidance directly contradicts industry narratives promoting new optimization acronyms like GEO, AEO, and LMEO as distinct disciplines. The team emphasized that all ranking systems reward content created primarily for human benefit rather than algorithmic manipulation, whether appearing in traditional blue links or AI-generated responses.

When: The podcast episode was recorded and published on December 17, 2025, following months of industry confusion about AI search optimization requirements. The guidance builds on blog post published in May 2025 after the Search Relations team consulted with engineers about what website owners should do differently for AI features.

Where: The message applies specifically to Google's search ecosystem, including traditional web search, AI Overviews operating in 200 countries and 40 languages, and AI Mode available in the United States and India. Sullivan explicitly stated the guidance does not cover other companies' AI search systems or conversational platforms.

Why: Google emphasized this message to address widespread confusion within the digital marketing community about whether AI-powered search demands new optimization approaches. The company wants website creators focusing on original, authentic content for human audiences rather than pursuing system-specific tactics that may fail as algorithms improve. Sullivan acknowledged natural reactions to format changes but stressed that chasing temporary advantages through specialized optimization often proves counterproductive as underlying systems evolve toward rewarding genuine quality.