It isn\u2019t. But that doesn\u2019t mean nothing has changed.<\/p><\/blockquote>\n
The noise around AI SEO right now is considerable, and most of it is pulling businesses in the wrong direction. Some are abandoning proven search strategies entirely in pursuit of something they don\u2019t fully understand. Others are paralysed, waiting for the dust to settle before doing anything at all. Neither response is particularly useful.<\/p>\n
What this article sets out to do is separate the genuine shifts from the hype, give you an honest picture of what SEO for AI search engines actually requires, and explain why the businesses that have been doing SEO properly all along are better placed than anyone else.<\/p>\n
What We Actually Mean by AI SEO<\/h2>\n
Before getting into strategy, it\u2019s worth being precise about what we mean when we talk about AI search.<\/p>\n
AI search refers to search experiences where results are generated by a large language model rather than returning a ranked list of links. Instead of ten blue links, the search engine synthesises an answer directly, drawing on content from across the web. Google\u2019s AI Overviews, Perplexity, ChatGPT Search, and Microsoft Copilot are all examples of this.<\/p>\n
AI-powered SEO, then, is the practice of ensuring your content and your brand are visible within those generated answers \u2014 not just in traditional search results.<\/p>\n
The distinction matters because the mechanism is different. A traditional search engine crawls, indexes, and ranks. An AI search engine ingests, comprehends, and synthesises. What it chooses to include in its answer depends heavily on which sources it trusts \u2014 and trust, as we\u2019ll come to, is built the same way it always has been.<\/p>\n Google introduced E-A-T \u2014 Expertise, Authoritativeness, and Trustworthiness \u2014 in its Search Quality Rater Guidelines in March 2014.<\/p>\n Source: Page One Power <\/strong>(https:\/\/www.pageonepower.com\/search-glossary\/eeat)<\/p>\n Most people didn\u2019t pay much attention at the time. It felt abstract. Then the Medic update in 2018 hit health and finance sites hard, and suddenly everyone wanted to understand what Google meant by expertise and trust.<\/p>\n In December 2022, Google expanded the framework by adding a second E for Experience, creating E-E-A-T. The addition was significant.<\/p>\n Source: Victorious<\/strong><\/a><\/p>\n It drew a clear line between knowing about something and having actually done it. A product reviewer who used the product demonstrates Experience. A journalist summarising product specs from a press release demonstrates Expertise, but not necessarily Experience. That distinction matters enormously in an era when AI can generate plausible-sounding content about almost anything.<\/p>\n EEAT is not a score. It\u2019s not a metric you can track in a dashboard. It\u2019s a quality framework that shapes how Google evaluates the credibility of content and the people and organisations behind it. Pages with strong EEAT signals are 2.3 times more likely to be cited in Google AI Overviews, according to a Wellows study analysing 2,400 AI Overview citations.<\/a><\/p>\n That figure tells you something important: the quality framework Google built over a decade to evaluate human-written content is the same framework its AI systems use to decide what to cite. The rules haven\u2019t changed. The stakes have.<\/p>\n The September 2025 update to the Search Quality Rater Guidelines<\/a> expanded the YMYL (Your Money or Your Life) definition and added new evaluation criteria specifically for AI Overviews.<\/p>\n These are refinements to a framework that has been in continuous development for over a decade, not a new set of rules.<\/p>\n\n\n\n\n![\"\"](\"https:\/\/markegy.at\/wp-content\/uploads\/2026\/10\/Trust-Venn-Diagram-embed-selection.png\")
<\/figure>\nEEAT: The Framework That Was Always Going to Win<\/h2>\n