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AI search · Foliora field guide

What is AI SEO? A practical definition for modern search

Understand how traditional SEO, AI-assisted SEO, GEO, and answer-engine optimization fit together—and where the work actually changes.

AI SEO has two different meanings

AI SEO can mean using artificial intelligence to perform search-engine optimization work, or optimizing a business so it appears accurately in AI-generated answers. Those are related but different jobs. A writing assistant can accelerate research and drafting; it does not automatically make a company a credible source.

Foliora uses AI SEO to describe the full system: preserve the technical foundations Google needs, map the questions buyers ask, publish evidence-rich answers on the company’s domain, and measure both search rankings and AI citations.

What stays the same

Search engines and answer systems still need accessible pages, clear information architecture, descriptive titles, crawlable links, stable canonical URLs, and claims supported by real evidence. AI interfaces change the result format, not the need for a trustworthy source.

  • Technical accessibility and indexability
  • Pages matched to real buyer intent
  • Original expertise, facts, and examples
  • Clear entities, authorship, and source relationships
  • Useful internal links between evidence and commercial pages

What changes for AI answers

A ranked blue link can win a click with a relevant title. An AI answer must also decide whether a passage is clear enough to extract, specific enough to trust, and appropriate to cite for the question being answered. That raises the value of direct definitions, bounded claims, first-party details, and visible sourcing.

The goal is not to write for a model instead of a person. The goal is to make expert information easier for both people and systems to understand without stripping away context or uncertainty.

A responsible operating loop

The safest approach separates research, judgment, approval, and execution. Models can synthesize research and draft changes, but deterministic checks should establish technical facts and a customer should approve material claims or production changes.

  • Research the market and current visibility
  • Build an evidence-backed strategy
  • Show the exact proposed change
  • Publish only after approval
  • Verify the live result and measure movement over time

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