Introduction to AI Search
Google has been constantly iterating to improve its product and stay ahead in the game. With the rise of large language models (LLMs) and generative AI chatbots, Google is evolving its interface to bridge the gap between AI and search. However, it’s essential to remember that Google has already been integrating AI into its algorithms for years.
The Evolution of Search
According to Ray Grieselhuber, CEO of Demand Sphere and organizer of Found Conference, "There is not really any such thing anymore as traditional search versus AI search. It’s all AI search. Google pioneered AI search more than 10 years ago." This statement highlights the significance of AI in search and how it has become an integral part of the search experience.
Why Grounding Data Matters
The conversation with Ray started with his recent post on LinkedIn, where he mentioned, "It’s the grounding data that matters, far more than the model itself. The models will be trained to achieve certain results but, as always, the index/datasets are the prize." Ray explained that unless something radically changes in how LLMs work, we’re not going to have infinite context windows. If you need up-to-date, grounded data, you need indexed data, and it has to come from somewhere.
The Importance of Indexing
Earlier this year, Ray and his team analyzed ChatGPT’s citation patterns, comparing them to search results from both Google and Bing. Their research revealed that ChatGPT’s results overlap with Google search results about 50% of the time, compared to only 15-20% overlap with Bing. This highlights the importance of indexing and the advantage Google has in terms of data and index size.
Human Behavior and Search
Ray made another recent comment online about how people search, saying, "Humans are searchers, always have been, always will be. It’s just a question of the experience, behavior, and the tools they use. Focus on search as a primitive and being found and you can ignore pointless debates about what to call it." This statement emphasizes the significance of human behavior in search and how it remains constant despite changes in technology.
The Role of Schema in LLM Visibility
Ray’s analysis reveals that LLMs don’t directly process schema in their training data, but there is some limited influence of structured data through retrieval layers when LLMs use search results as grounding data. Google has essentially trained the entire internet to optimize its semantic understanding through schema markup. However, Ray stressed that schema is only being used as a hint, and it shouldn’t be a question of does this work or not – should we implement Schema to influence results? Instead, SEOs should be focusing on the impact on user and human behavior.
Attracting Human Attention Through Search Behavior
Binary thinking, such as SEO is dead, or LLMs are the new SEO, misses the reality that search behavior remains fundamentally unchanged. Humans are searchers who want to find information efficiently, and this underlying need remains constant. Ray said that what really matters and underlines SEO is to attract human attention through their search behavior.
An Industry Built for Change
Despite the disruption, Ray sees opportunity. SEOs are uniquely positioned to adapt. Success in the age of AI-powered search isn’t about mastering new tools or chasing the latest optimization techniques. It’s about understanding how people search for information, what experiences they expect, and how to provide genuine value throughout their journey, principles that have always defined effective marketing.
Conclusion
In conclusion, the rise of AI search is not a replacement for traditional search, but rather an evolution of the search experience. Google has been integrating AI into its algorithms for years, and it’s essential to understand the significance of grounding data, indexing, and human behavior in search. By focusing on attracting human attention through search behavior and providing genuine value, SEOs can adapt to the changing landscape and thrive in the age of AI-powered search.