Generative Engine Optimization

Generative Engine Optimization (GEO) is the practice of making your brand visible in AI-generated answers. Where SEO optimizes for search engine result pages (SERPs), GEO optimizes for the AI-generated responses that increasingly replace them.

Why GEO Matters

When someone asks ChatGPT, Perplexity, or Google's AI Overview a question, the AI synthesizes an answer from its training data and cited sources. GEO ensures your brand and content are among those sources.

Research shows that 82-89% of AI-generated answers reference third-party publications — not brand-owned content. This means earned authority is the primary lever for GEO, not on-page technical optimization.

GEO vs. SEO

SEO	GEO
Optimize for keyword rankings	Optimize for AI citations
Target search result pages	Target AI-generated answers
Backlinks as signals	Entity authority as signals
On-page content	Cross-platform presence
Measure by rank position	Measure by citation frequency

Key GEO Techniques

1. Earned media in authoritative publications — AI engines heavily weight tier-1 sources
2. Entity signal strengthening — Schema markup, Knowledge Graph, Wikipedia presence
3. Citation-optimized content structure — Clear claims, statistics, expert quotes that LLMs extract
4. Multi-source corroboration — The same facts appearing across multiple trusted sources
5. Freshness signals — Recent, updated content is preferred by AI engines

GEO vs. AEO

GEO is the broader discipline; Answer Engine Optimization (AEO) is a subset focused specifically on answer engines like Perplexity and Google AI Overviews where a single definitive answer is surfaced. Both fall under the Machine Relations framework.

GEO in Practice

AuthorityTech pioneered GEO as a core component of Machine Relations. The AI Visibility Audit measures your current GEO performance across major AI engines — tracking share of voice and citation gaps against competitors.