John Mueller’s advice on how to appear in AI overviews.

Why the May 2025 Blog Post is Just Old SEO Advice with a New Wrapper.

Google's recent Search Central blog post on how to appear in AI Overviews and AI Mode has been making the rounds. Authored by John Mueller, it promises insight into succeeding in the age of AI search. But once you peel back the polished language, you're left with a frustrating realisation: this is standard SEO advice dressed up as something new.

TLDR
The advice given is nearly indistinguishable from what Google published around:

•   Panda (2011): focus on quality
•   Hummingbird (2013): focus on intent
•   BERT (2019): focus on nuance
•   Helpful Content Update (2022+): focus on people first content

The blog offers no new mechanisms, tools, or insights into how to actually optimise for AI Overview inclusion.

1. It's the Same ‘Helpful Content' Sermon

The post opens with a familiar refrain: “Focus on your visitors and provide them with unique, satisfying content.” If you've been in SEO for more than a week, you've heard this before. It sounds profound until you realise it's the same platitude they've been pushing since Panda. There is no insight into what actually makes content rank in AI Overviews, just a vague nod toward being “people-first.”

2. Technical SEO Basics Rebranded as AI Strategy

You're told to make sure Googlebot isn't blocked, that your pages return a 200 status code, and that your structured data matches your content. This isn't AI-specific guidance; this is basic technical SEO hygiene. Suggesting this is somehow a strategy for AI Mode is disingenuous at best.

3. The Multimodal Mirage

Yes, Google mentions that you should use images and video because users might do “multimodal” searches. But again, this is not new. We've known for years that visual content helps with engagement, rankings, and rich results. Calling it an AI insight is marketing spin.

4. What’s Supposedly New (But Isn't)

Here's a breakdown of what Google claims is new, and why it's really just old advice repackaged:

5. No Real Answers About How AI Overviews Work

What triggers inclusion in an AI Overview? How is content selected, summarised, or excluded? What role does structured data play vs. on-page semantics? The blog post answers none of these questions. Instead, it advises you to “focus on content quality” and consider using nosnippet if you want out.

6. AI SEO vs. Traditional SEO: The Real Difference

There's a growing debate: is AI SEO fundamentally different from traditional SEO? According to Google, not really. Their stance: “If you're already making great content, you're covered.”

But here's the catch: AI Overviews don't rank pages. They generate summaries, pulling semantic snippets from sources they trust. The inclusion mechanism is different, even if the surface-level advice remains the same.

Traditional SEO Focus:

• Backlinks
• Keyword optimisation
• Meta tags
• Crawlability
• Author reputation

AI SEO Focus:

• Entity resolution
• Semantic clarity
• Structured content
• Summary-worthiness
• Trust and transparency markers

So yes, the rules are the same, but the gameboard has changed.

7. The Gameboard Has Changed: What That Really Means

In traditional search, your goal was to rank. To be in the top 10 blue links, to win snippets, to attract clicks through positioning. The entire SEO playbook was built around that premise: optimise for crawlability, authority, and keyword relevance to influence ranking positions.

In AI search, the game is about selection and synthesis. You're not being ranked, you're being extracted. The system is not choosing “the best 10 pages,” it's generating an answer and cherry-picking fragments of content that can support that answer.

What this means for SEOs:

• Position doesn't matter as much. You can appear in an AI Overview without ranking in the top 10.
• Entity clarity matters more. Google needs to understand what your page is about and who it's coming from.
• Summarisability is the new king. Clear, authoritative, fact-stated content has a higher chance of being picked up.
• Structured markup is now foundational, not optional. It feeds the semantic layer powering AI summaries.
• Trust markers (authorship, sources, transparency) are now direct signals. If your site hides behind anonymity or lacks E-E-A-T signals, you're less likely to be pulled in.

So while Google insists “nothing has changed,” in practice lots has. The optimisation goal has shifted from ranking to inclusion, from keyword revelancy to semantic clarity and from page performance to snippet suitability.

8. Conclusion: Look at the Results, Not the Sermons

If you're trying to rank in AI search, stop listening to surface-level PR. Instead, analyse which types of content actually appear in AI Overviews. Study their structure, their trust signals, their layout. Google isn't going to hand you the algorithm, but they will show you the results.

The real lesson? Google's AI search guidance is more of a press release than a playbook. If you're serious about succeeding in this space, you'll need to reverse-engineer, test, and iterate.

Action items: If you do a search for “who is” and your own name, see what it does and what it pulls in. You'd hope that you'd have a good idea where you appear personally on the internet. You can see what type of content it pulls in about you, and maybe that would give you some hints on how the overall algorithm works.

And if you do crack the algorithm, maybe try and exploit the alpha yourself rather than tell people and let them spam it to death.

Ben

Ben Luong is a technical marketing consultant who operates where AI falls short. In a world flooded with cheap, mediocre code and automated strategies, he provides the expert integration, verification, and strategic accountability required to make modern marketing stacks profitable. He specialises in architecting Google Ads, SEO, and GA4 into a single, high-performance system that is accountable to the bottom line.