Is SEO on a Dying Path? Google Weighs In

Google’s latest Search Off the Record podcast tackled the question of whether SEO is “on a dying path” due to the rise of AI Search. The discussion aimed to clarify Google’s stance on the matter, suggesting that SEO remains largely unaffected by the introduction of AI-driven search technologies.

However, this view contrasts with the real-world experiences of many digital marketers and publishers. While Google maintains that SEO fundamentals have not changed, the challenges and shifts observed by industry professionals suggest otherwise.

Google Speculates If AI Is On A Dying Path

During the podcast, the conversation shifted to AI when John Mueller raised a question about its potential impact on SEO. He asked, “Do you think AI will replace SEO? Is SEO on a dying path?”

Gary Illyes responded with scepticism, pointing out that SEOs have been predicting the demise of SEO for decades. He reassured listeners that SEO is not in danger, stating: “SEO has been dying since 2001, so I’m not scared for it. I’m pretty sure that, in 2025, the first article that comes out is going to be about how SEO is dying again.”

Gary’s observation holds some truth. Google has been refining its approach to SEO since around 2004, gradually challenging the SEO strategies of the time. By 2005, statistical analysis began to influence how SEO was approached. The search landscape today is radically different from its early days, and it stands on the brink of significant transformation as we head into 2025.

RAG Is The Gateway To AI-SEO

During the podcast, Lizzi Sassman raised the question of how SEO will remain relevant in 2025. After some light-hearted banter, John Mueller brought up the topic of RAG, or Retrieval Augmented Generation.

RAG is a technique used by large language models (LLMs) to provide up-to-date, factually grounded answers. This system retrieves relevant information from external sources such as search indexes or knowledge graphs, which the LLM then uses to generate responses. Essentially, Retrieval-Augmented Generation enhances the way information is gathered and utilised.

To explain RAG further, Googler Martin Splitt offered an analogy. He likened it to documents (representing the search index or knowledge base), with search and retrieval playing a role in extracting information from those documents. He described it as an output of information, which can be imagined as “something out of the bag.”

Martin’s simplified analogy was as follows: “Probably nowadays it’s much better and you can just show that, like here, you upload these five documents, and then based on those five documents, you get something out of the bag.”

Lizzi Sassman responded by clarifying: “Ah, okay. So this question is about how the thing knows its information and where it goes and gets the information.”

John Mueller continued the discussion, emphasising how RAG ties SEO practices to AI search engines. He explained that there is still a search engine ranking process that plays a role in these new systems. Even AI-driven search engines, such as Perplexity AI, still use an updated version of Google’s old PageRank algorithm as part of their ranking process.

Mueller elaborated: “I found it useful when talking about things like AI in search results or combined with search results where SEOs, I feel initially, when they think about this topic, think, ‘Oh, this AI is this big magic box and nobody knows what is happening in there.’ And, when you talk about kind of the retrieval augmented part, that’s basically what SEOs work on, like making content that’s crawlable and indexable for Search and that kind of flows into all of these AI overviews.”

He continued, explaining that AI-powered search results often combine the existing methods that SEOs are already familiar with. In this way, SEO is not suddenly rendered obsolete by AI; the practices of crawling, indexing, and ranking continue to play a vital role.

Mueller’s insight shows that traditional SEO methods still underpin much of AI-driven search processes. This perspective suggests that while AI may introduce new elements to search engines, it does not fundamentally change the importance of SEO. It serves as a reminder that SEO remains relevant and crucial for making websites discoverable and optimised for search engines. However, it’s clear that AI’s growing influence does mean some changes are inevitable.

The Impact Of AI On SEO

While crawling and indexing remain largely unchanged, AI in Google’s ranking algorithms now make decisions based on opaque signals such as helpfulness, authority, and, ironically, whether content is created for humans or machines. This shift in focus is what truly matters.

The reality is that crawling and indexing do little to help the thousands of small and large publishers who have been driven out of the web ecosystem due to algorithm changes. Publishers have faced challenges such as preferential ranking for less authoritative Reddit content and the de-prioritisation of expert content in favour of AI-generated summaries.

There are at least three key ways AI has reshaped the SEO landscape for publishers:

Organic SERPs are explicitly obsolete
Natural language search queries are changing relevance
Capricious AI ranking algorithms undermine web ecosystem stability

Organic SERPs Are Explicitly Obsolete

While the traditional “ten blue links” have been implicitly obsolete for about 15 years, AI has now made them explicitly so. The shift towards AI-driven search results signals a fundamental change in how search engines rank and display content.

Natural Language Search Queries

One of the most significant changes is the way search users now ask precise conversational questions through multiple interactions. Bing claims that this shift makes it easier to understand and respond to search queries with increasing precision. For SEOs and publishers, this is unsettling because a substantial amount of content was created to rank in the keyword-based query paradigm, which is slowly fading away. As users shift towards more complex queries, the challenge for content creators is how to adapt and optimise for these new types of searches.

Backend AI Algorithms

The term “capricious” refers to a tendency to make sudden and unpredictable changes, and it’s not a quality that benefits publishers and SEOs who thrive on relatively stable and reliable search engine ranking factors. Unfortunately, this is precisely what we’re seeing with AI-powered ranking algorithms. These algorithms can abruptly change their decisions, determining that content deemed relevant last month is no longer of value today. And just when publishers adjust to one set of criteria, the ranking algorithms might change again, leaving them scrambling to catch up.

The frequent, radical changes to Google’s ranking algorithms suggest that no iteration is ever truly final, creating an unstable environment for publishers and SEO professionals trying to keep up with the constant shifts.