Practices intended to improve how a brand or its content is discovered, represented, and cited in AI-generated responses (ChatGPT, Claude, Perplexity, Gemini).
Generative engine optimization, or GEO, is an industry label for work intended to improve how a business or its information is discovered and represented in generated answers. The label can cover content quality, technical access, factual consistency and measurement. It is not one standardized process shared by every AI service.
A useful plan starts with the actual information a business can provide. Clear descriptions, supported claims and well-maintained resources help people evaluate an offer regardless of how they arrive. Formatting alone cannot guarantee that a system will retrieve the page, cite it correctly or recommend the business.
Measurement should distinguish several outcomes. Being named is different from receiving a citation, and both differ from a recommendation or a visit. A provider promising GEO results should explain the platforms, questions, sampling method and evidence involved. Otherwise a favorable isolated answer can be mistaken for a broad, durable improvement.
Takeaway: Ask for concrete content, access and measurement work behind a GEO proposal. Avoid guaranteed AI recommendation claims or tactics that depend on misleading information.
Example
A specialist wholesaler improves its compatibility tables, documents the source of product specifications and records answers to a consistent set of purchasing questions. It tracks whether generated answers cite the correct resource and preserve its limits, rather than counting every incidental brand mention as a qualified lead.
What to check
Keep platform-specific controls and observations separate. Google’s guidance for its AI search features should not be assumed to describe every other provider. Review actual answers and sources before attributing a change to a particular edit or reporting a universal AI visibility score.
For more detail, see Google AI feature guidance.