5 SEO truths that cut through the AI noise

While some SEO influencers are selling panic and “AI-proof” gimmicks, the data from Google’s front lines tells a different, more strategic story. 

The rapid integration of AI into search has created a wave of anxiety, making it increasingly difficult to distinguish between durable strategy and distracting noise. 

The flood of information often leaves marketers unsure of where to focus their efforts.

That’s the diamond in the rough that I discovered while attending the News & Editorial SEO Summit (NESS), which was held online Oct. 21-22. 

This article cuts through the hype to deliver clarity. 

I’ve distilled insights from technical SEO experts at The New York Times, Polemic Digital, and NewzDash into five counterintuitive but actionable truths. 

These takeaways offer a durable, data-backed framework for your 2026 SEO strategy and beyond.

1. AI Overviews aren’t devouring breaking news (yet)

Contrary to the widespread belief that AI Overviews are taking over every SERP, the data reveals a far more nuanced reality for timely content. 

A detailed analysis from NewzDash found that only 1.9% of major trending news keywords trigger AI Overviews. 

For the most competitive, high-traffic moments, traditional search features still dominate.

The real “surprising truth” is in the context of when and why AI Overviews appear.

AI Overviews are most likely to show up 6 to 9 hours after a major news event, during the “post-event window” when live interest fades and real-time coverage slows. 

The analysis identified several key signals that increase the likelihood of an AI Overview, including:

• Low-competition queries.
• Broad entity searches without qualifiers (e.g., “Chicago” instead of “Chicago shooting”).
• Topics with little or no immediate coverage. 

This insight is critical: for now, Top Stories and real-time reporting still command the SERP during the moments that matter most, countering the narrative that AI has completely replaced traditional news results.

Dig deeper: AI Overview citations: Why they don’t drive clicks and what to do

2. Your ‘good enough’ Core Web Vitals are probably fine

The obsession with achieving perfect Core Web Vitals (CWV) scores can lead to diminishing returns. 

While important, CWV is not the massive direct ranking factor many believe it to be. Its primary role is as an indicator of usability and user experience.

The real impact of CWV is indirect but potent. 

Poor CWV creates a frustrating user experience. 

Frustrated users leave or click back quickly. 

Google interprets these behaviors as negative engagement signals, which can directly harm your rankings. 

Think of CWV as a tool to measure and prevent user experience problems.

The practical advice from industry experts is to get your scores to “Mostly green.” 

Investing significant resources to improve further is rarely worth the effort from a pure SEO perspective.

3. Stop obsessing over clean code – focus on meaning

Engineers often obsess over minimizing every byte in the HTML, a holdover from the days of slow connections. 

But Google’s crawlers don’t care. 

The surprising truth is that “clean source code is not necessary.”

The technical reason is that Google tokenizes HTML before parsing, stripping out non-semantic tags that don’t add meaning. 

Instead of wasting engineering cycles on superficial code cleanup, reallocate those resources to what actually moves the needle: robust semantic markup.

Using tags like <article>, <section>, and <nav> explicitly tells Google what each block of content represents. 

This makes indexing easier and reduces the chance of errors by clearly defining the purpose and relationship of your content.

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4. Content chunking is your new AI superpower

As search evolves from bots to large language models (LLMs), structuring content for machine comprehension is more important than ever. 

Content chunking has emerged as a critical practice for ensuring your content is visible and usable by AI systems. 

This structure is crucial for the operation of modern AI systems, particularly those using retrieval-augmented generation (RAG). 

RAG needs to fetch verified data to “ground” its responses, and well-chunked content makes your information a prime candidate for retrieval.

To make your content easy to chunk, you must provide a clear, logical structure. 

You can do this by following two key principles:

• Anchor chunks with semantic HTML5 tags: Use tags like <article>, <section>, <nav>, and <footer> to explicitly define the different parts of your page.
• Establish a clear hierarchy with header tags: Using <h1> through <h6> tags correctly creates logical topical breakpoints that guide the LLM’s understanding of your content’s structure.

A simple rule of thumb offered by Christine Liang of The New York Times is: 

• “If a chunk makes sense to you as a reader, then it makes sense for the LLM.”

Dig deeper: Chunk, cite, clarify, build: A content framework for AI search

5. Don’t fall for the latest AI SEO gimmicks

In the rush to adapt to AI, many unproven and ineffective tactics have emerged. 

Focus on foundational principles rather than chasing the latest gimmicks.

For instance, LLMs.txt, a proposed standard for guiding AI crawlers, is “not a thing – at least not for Google,” according to experts. 

Its adoption by both websites and LLMs is very low, making it an ineffective tool. 

Similarly, tactics such as over-optimizing content with endless lists, FAQs, and aggressive front-loading are essentially a modern version of classic keyword stuffing. 

While they may offer short-term gains, their effectiveness will diminish as models get smarter and better at understanding naturally written content.

The foundation of AI visibility remains grounded in traditional SEO. As Gary Illyes of Google told Kenichi Suzuki in a recent interview:

• “As far as I know, Gemini AI Overview and AI Mode all use Google search for grounding. So, basically, they issue multiple queries to Google search and then Google search returns results for that those particular queries.”

This is the most important statement for SEOs today. 

It confirms that AI Overviews are built upon the foundation of traditional Google Search. 

The path to visibility in AI features runs directly through mastering the fundamentals of SEO, not chasing shiny objects.

The real path to AI visibility still runs through core SEO

While the search landscape is undoubtedly being reshaped by AI, the core pillars of effective SEO are not just relevant – they’re more critical than ever. 

A strong technical foundation, semantically structured content, a commitment to quality, and a focus on user experience are the principles that endure. 

These are the signals that both traditional search crawlers and sophisticated AI models rely on to identify authoritative and valuable information.

In an age of increasing complexity, mastery of the fundamentals is the ultimate competitive advantage. 

Instead of asking how to “optimize for AI,” the real task is to create content so valuable and well-structured that both humans and AI have no choice but to cite it.

Dig deeper: AI search is booming, but SEO is still not dead