Search engine optimisation (SEO) has undergone a significant transformation over the past two decades, evolving from a focus on persuading search engines to a broader mission of educating artificial intelligence (AI) systems. What began in 1998 as a way to influence platforms such as Google, Bing, and Yahoo has expanded into a discipline that now encompasses AI-driven tools and recommendation engines.
By 2023, SEO was defined as “the art and science of persuading recommendation engines – including Google, Bing, ChatGPT, Perplexity, Siri, Alexa, and Copilot – to present your solution as the best in the market.” Two years later, this definition has shifted again. Today, SEO – also referred to as generative engine optimisation (GEO), answer engine optimisation, or AI assistive engine optimisation – is described as “the art and science of engineering a brand’s entire digital ecosystem to educate AI assistive engines, ensuring the brand becomes their most trusted, logical, and go-to answer at every stage of the conversational acquisition funnel.”
This new perspective raises an important question: if modern SEO is about teaching AI, where should businesses look to understand how these systems learn?
Google is the blueprint for AI learning
Despite concerns that Google is losing ground in online search, it remains the most complete ecosystem for understanding the direction of AI assistive engines. Unlike its competitors, Google integrates all three pillars of what experts call the “algorithmic trinity”: a constantly updated web index, a factual knowledge graph, and a large language model (LLM) capable of natural conversation.
For brands, the task is to create clarity within this framework. AI is likened to a child – eager to learn but prone to confusion. It absorbs information from a brand’s digital footprint through three perspectives: what is current (search results), what is factual (the knowledge graph), and what is conversational (the LLM).
To teach effectively, brands must build their curriculum across three areas: conversation, knowledge, and timely information. This requires a structured approach that transcends traditional, channel-specific tactics, because AI draws from the entire digital ecosystem rather than isolated elements.
Building clarity, credibility and deliverability
Success in this new environment depends on a repeatable methodology built on three pillars: understandability, credibility, and deliverability. Understandability requires brands to define clearly who they are, what they offer, and whom they serve. Credibility involves demonstrating expertise, authority, trustworthiness, and transparency across platforms. Deliverability ensures that the right content reaches the right audience at the right time.
Together, these three phases foster algorithmic trust and position a brand at the forefront of AI-driven recommendations.
This approach aligns with the concept of the Conversational Acquisition Funnel, which covers three key stages of user engagement. At the top of the funnel, clarity ensures visibility during the awareness stage. AI engines are more likely to recommend a recognised expert with well-defined authority than a vaguely described entity.
In the middle of the funnel, credibility is vital for consideration. Here, AI engines weigh not only what is said but also who is saying it. Ambiguous or inconsistent classifications reduce the likelihood of being presented as a trusted option. At the bottom of the funnel, understandability ensures that a brand is consistently represented across the web, allowing AI to recommend it as the ultimate choice confidently.
The evolving role of SEO professionals
Google’s June 2025 Knowledge Graph update emphasised the importance of clarity, marking a shift in how SEO professionals define their work. The focus is no longer on persuading algorithms with tactics but on educating them systematically.
Industry observers suggest this shift represents the greatest opportunity since Google established its dominance in the search engine market. With AI assistive engines increasingly shaping how people discover, evaluate and choose solutions, brands that position themselves as educators stand to build lasting algorithmic trust.
Those that succeed will remain top of mind for AI systems, consistently recommended as the reliable answer across countless conversations with users worldwide.
