Search just turned into a synthesis problem.
Optimize for the new mechanics.

AI search optimization is the practice of structuring your website, content, and external evidence so AI-powered search engines can identify and assess it when users ask category-relevant questions. It is the operational discipline beneath the marketing term 'GEO'. Where traditional search returns ranked links, AI search may return one synthesized answer with cited sources. The work improves source eligibility, while each engine independently decides what to retrieve and cite.

Three architectural differences. First, retrieval: traditional search retrieves a ranked list of documents; AI search retrieves a smaller set of documents and synthesizes them into a single response. Second, presentation: traditional search shows you the documents and lets you choose; AI search shows you an answer and a citation footer. Third, intent: traditional search assumes the user will click through and read; AI search assumes the user has already gotten what they need by the time they finish reading. The optimization implications cascade from there: schema becomes more important than meta descriptions, citation density beats keyword density, and entity disambiguation beats page-level relevance.

All five major engines, with priority based on your audience. Google AI Overviews appears above the organic results on roughly 13% of queries (and growing): biggest near-term opportunity. ChatGPT has 300M+ weekly active users and is now the dominant top-of-funnel research engine for B2B buyers. Perplexity sends meaningful click-throughs because every answer cites sources by default. Gemini integrates across Google Workspace and is the default for many enterprise users. Claude (which we use ourselves) drives a smaller but extremely high-intent technical audience. Optimize for all five: the underlying patterns largely overlap, but tune emphasis to where your buyers actually live.

Yes, with significant overlap. ChatGPT browses Bing's index plus a curated source list. Perplexity browses an internal index that draws from the broader web with a strong recency bias. Gemini draws from Google's index, so traditional Google SEO directly influences Gemini visibility. Claude's web tool uses Brave and similar privacy-respecting search infrastructure. Google AI Overviews pulls from Google's indexed pages, weighted toward sites with strong E-E-A-T signals. Strong baseline SEO (Google + Bing) underpins all five. The differences are most pronounced in citation behavior, not retrieval source.

Schema graph and FAQ markup are useful starting points. A site-wide @graph JSON-LD that chains Organization to Person to Article or Service helps AI engines identify the entity and who is responsible for the content. FAQ markup should match the visible answer exactly. Direct-answer paragraphs, citation-friendly evidence blocks, and question-formatted H2s can then make important passages easier to retrieve. The right sequence depends on the baseline, and no individual change guarantees citation movement.

We use Outrigger, the separate AI-visibility joint venture Joel co-founded with Andrew, to monitor 30-50 priority keywords across all five engines weekly. For each keyword, the dashboard tracks: was your brand mentioned, was it cited with a link, what was the citation context, what was the sentiment, which page was the source, and how does your citation share compare to the top three competitors. The composite output is a citation share percentage: your share of voice across AI answers in your category, tracked over time. We report this monthly alongside traditional GSC and GA4 metrics.

You can do the on-site portion yourself if you have a senior in-house operator: schema graph, FAQ markup, llms.txt, direct-answer paragraphs, question-formatted H2s. The harder workstream is external: earning third-party citations from tier-1 publications, expert-comment placements, original-data research that journalists quote. That's the work that compounds long-term, and it's the work most in-house teams don't have the relationships or production cadence to run consistently. Most agencies (us included) earn fees on that workstream, not the on-site retrofit.

There is no fixed result window. Each engine refreshes sources differently, while your starting rankings, entity clarity, authority profile, and query competition all affect timing. We baseline the priority queries, fix the clearest technical and content gaps first, and monitor each engine separately so the reporting shows what changes and what does not.