A useful definition
Generative engine optimisation is the work of making a company’s reliable information easier for AI-driven discovery systems to retrieve, understand and cite. It is sometimes called AI-search optimisation or answer-engine optimisation.
GEO is not a secret markup or a guaranteed way to appear in a model response. It depends on accessible source pages, clear entities, first-hand information and a wider reputation footprint.
SEO remains the foundation
Google’s guidance for generative AI features says core SEO practices remain relevant because AI search experiences draw on the search index and ranking systems. That means crawlability, useful content and accurate context still matter.
The best starting point is often not a new “GEO page”. It is improving the primary service pages, expert articles, case evidence, author information and organisation details that answer systems may use as sources.
What changes in the work
Traditional keyword pages often target a short query. AI-assisted research is more conversational and may break a question into several sub-questions. Useful source content therefore benefits from explicit definitions, comparisons, constraints, examples and evidence.
A strong page should be quotable without becoming simplistic: state the answer, show why it is true, describe limits and connect it to first-hand experience.
What to measure
Look for referral traffic from answer engines where visible, branded search growth, cited pages, assisted conversions and sales conversations that mention AI research. No single dashboard captures the whole journey.
Avoid chasing hundreds of near-duplicate question pages. Unique, non-commodity expertise is more defensible than scaled summaries.
How this becomes a project
A useful next step is a short audit of your current pages, search footprint, proof and measurement. The output should identify the few constraints worth fixing before more content or media is added.