Google Says AI Search Fundamentals Are Still SEO Fundamentals - Here’s What Actually Matters

For the past two years, the SEO industry has been flooded with “AI search hacks,” speculative frameworks, and technical silver bullets claiming to unlock visibility in AI-powered experiences.

Now, Google has made its position clear: the fundamentals that help websites perform well in traditional search are the same fundamentals that help them succeed in AI-driven search experiences.

That shouldn’t really come as a surprise.

At StudioHawk, this has consistently been our stance on AI SEO.

While search interfaces are evolving rapidly - from AI Overviews to conversational search and emerging agentic commerce experiences - the underlying systems still reward quality, trust, technical accessibility, and genuinely useful content.

What has changed is the speed at which these systems are evolving and the different nuances that were less relevant to the traditional algorithm - retrieval systems and RAG, chunking, vector embeddings, grounding, etc.

That means two things can be true at once: the core principles of SEO still matter enormously, but SEO teams also need to actively test, adapt, and validate assumptions as AI systems evolve.

That’s exactly how we approach modern search strategy at StudioHawk.

We are constantly running experiments across our own websites and testing environments to better understand how AI systems interpret content, entities, authority signals, product information, and technical structure.

Because while the foundations remain stable, the way search systems surface and synthesize information is changing rapidly.

The Industry’s Obsession With “AI SEO Hacks”

Whenever search evolves, the industry tends to respond the same way: find the shortcut first and ask questions later.

We saw it during the rise of mobile-first indexing. We saw it again with Core Web Vitals and voice search which still hasn’t taken off despite that meant to be causing the death of SEO years ago. Now we’re seeing the exact same cycle happen with AI search.

The problem is that much of the conversation around “ranking in AI” is currently being driven by theory rather than evidence.

There are endless discussions around AI crawler optimization, hidden prompts, markdown-only websites, custom AI files, and other supposedly revolutionary tactics.

Some of these ideas may eventually become meaningful. But right now, there is very little credible evidence suggesting they create stronger, more sustainable visibility gains than simply executing strong SEO fundamentals exceptionally well.

That’s not a particularly flashy answer, but it’s the reality.

However - what is true is that we are seeing a bigger reliance on SEO moving closer into the brand and overall marketing funnel. This is how SEO should have always been treated but for budget purposes it is generally split out.

We are seeing the importance of third-party credibility, more brand citations and therefore the importance of services like Digital PR playing ball with SEO (again as it always should have been) and “owned” audiences.

What Actually Matters in AI Search Right Now

While the interfaces are evolving, the core signals that help search systems understand and trust websites remain surprisingly familiar. The businesses seeing the strongest visibility gains across AI-driven search experiences are usually the ones already investing in high-quality SEO foundations.

Product Data Is Becoming Increasingly Important

As search evolves into more AI-assisted shopping experiences, product information is becoming significantly more important.

AI systems can only recommend, compare, and surface products effectively if they can clearly understand the data behind them.

That means clean product feeds, accurate specifications, consistent pricing, proper categorization, and well-structured merchant data are becoming foundational requirements rather than optional ecommerce enhancements.

This becomes even more important as we move toward agentic commerce experiences, where AI systems may increasingly assist users with product comparisons, recommendations, and purchasing decisions directly within search journeys.

Structured Data Still Helps Machines Understand Your Website

Schema markup has never been a magic ranking tactic, and that hasn’t changed with AI search.

What structured data does do well is reduce ambiguity.

It helps search engines better understand your products, organization, authors, reviews, services, and overall content relationships. In AI-driven environments where systems are synthesizing and interpreting information dynamically, that additional clarity matters.

The goal is not to “game” AI systems with schema. The goal is to make your website easier to interpret.

Technical SEO Still Creates Competitive Advantage

One of the more interesting things about the AI search conversation is how often technical SEO gets overlooked, despite still being incredibly important.

AI systems still rely on crawling, rendering, and processing websites efficiently. If your site is slow, bloated, difficult to crawl, or filled with low-value pages, you are creating friction for both users and machines.

The websites that consistently perform well in search - including AI-powered search experiences - are rarely technically chaotic. They tend to have strong architecture, efficient rendering, clean internal structures, and clear pathways for both users and bots to navigate content.

Technical SEO remains one of the clearest competitive advantages because it improves accessibility, discoverability, and usability simultaneously.

Content Quality Matters More, Not Less

One of the biggest misconceptions around AI search is the idea that content quality somehow matters less now that AI can generate content at scale.

In reality, the opposite is happening.

As generic content becomes easier and cheaper to produce, genuinely useful content that offers a specific point of view or proprietary data or opinion becomes more valuable.

The strongest-performing content today tends to demonstrate real expertise, original thinking, topical depth, and actual information gain rather than simply rewording what already exists online.

This is where many businesses are getting AI content strategies wrong. The issue is not using AI itself - AI can absolutely improve workflows and efficiency.

The issue is publishing large volumes of lightly edited or entirely unreviewed AI-generated content that lacks expertise, differentiation, and quality control.

Human insight still matters enormously. Strategy still matters. Editorial judgment still matters.

The brands succeeding in modern search are generally using AI as an enhancement layer, not as a replacement for expertise.

There’s been a lot of noise around “chunking”. This is essentially passage indexing - a concept introduced into English search engines by Google back in February 2021. It was one of the first topics I ever spoke about publicly on Crawl Error’s webinar back in January 2021.

This is still important. Clear structure, non-waffly content, making a succinct point and then backing it up with evidence. This should have always been a fundamental part of content creation - which many SEO’s without a content or journalistic background missed over the years.

Internal Linking and Site Structure Still Matter

Internal linking remains one of the most overlooked areas of SEO despite being incredibly valuable for both traditional and AI-driven search systems.

A strong internal linking framework helps search engines better understand topical relationships, content hierarchy, and site architecture. It also helps distribute authority throughout the website and improves crawl efficiency.

For AI systems attempting to understand your expertise and topical authority, these contextual relationships matter far more than many people realize.

Authority and Brand Signals Are Becoming Even More Important

As the internet becomes increasingly saturated with AI-generated content, authority signals are becoming even more valuable.

Search systems still rely heavily on external validation to determine credibility and trustworthiness. That includes backlinks, editorial mentions, digital PR, expert citations, brand references, and broader reputation signals across the web.

At the same time, owning a clear niche and building a recognizable brand is becoming a major competitive advantage.

The businesses most vulnerable to AI disruption are often the ones producing interchangeable content without a distinct perspective or identity.

Meanwhile, brands with strong topical ownership, recognizable expertise, and genuine authority continue to perform well because they give search systems stronger trust signals to work with.

The Problem With Speculative AI SEO Tactics

This is where the industry needs a bit more balance.

There’s nothing wrong with experimentation. In fact, experimentation is essential right now because the technology is evolving quickly. We actively test emerging concepts ourselves because understanding how these systems change is incredibly important.

But there’s a major difference between testing hypotheses and presenting speculation as a proven strategy.

Take llms.txt as an example. There is currently very limited evidence showing that implementing it materially improves visibility within AI search systems even though there are some claims that it does make a difference with Claude. According to some tools like Peec who play clearly in the AI space, this particular tactic is a distraction unless your main target audience is vibe coders and AI coding tools.

The same applies to claims that converting entire websites into markdown creates major ranking advantages.

Could some of these ideas become more relevant over time? Absolutely.

But right now, many businesses would see far greater returns investing in technical quality, structured information, stronger branding, better content, and improved site architecture than chasing speculative AI optimization tactics with limited supporting evidence.

The Future of AI Search Still Belongs to Strong SEO

One of the biggest misconceptions in the industry right now is the idea that AI search is replacing SEO.

If anything, AI search is reinforcing the importance of good SEO.

The websites most likely to succeed in AI-driven environments are usually the same websites already investing in technical excellence, topical authority, strong branding, high-quality content, and excellent user experiences.

The fundamentals are not disappearing.

They are compounding.

Final Thoughts

Google’s latest guidance reinforces something experienced SEO professionals have understood for a long time: sustainable visibility is still built on strong foundations.

There is no universal AI search hack replacing expertise, authority, technical quality, or genuinely useful content.

Our view remains the same as it has always been. The fundamentals matter enormously, but so does staying adaptable as search technology evolves.

That’s why we continue testing, learning, and evolving alongside these systems while remaining grounded in the core principles that have always driven long-term organic growth.

Because the businesses that ultimately win in AI search will not be the ones chasing every speculative tactic.

They will be the ones building genuinely authoritative, technically strong, deeply useful brands that search systems - and users - can trust.

N.B. There have long been examples of Google’s documentation not being the full story, as seen with the leaked Google algorithm documents so it’s important we take their guidelines with a pinch of salt. What works for Google is not necessarily what’s going to work for ChatGPT, Claude and other LLMs / AI Systems. This is where continuous testing across platforms remains vital.