AI Search Optimization: 9 Tactics Ranked

AI search optimization is the work of making your pages easy for AI search systems to fetch, understand and quote in a generated answer. Most guides give you a flat list of tips. This one ranks nine tactics by effort and by which half of the job they touch: getting retrieved or getting cited.

It is for marketers and site owners who already have a working website and want to spend limited time on the changes that matter. The ranking is our judgment, built on Google’s and OpenAI’s documentation and two published studies. We say where the evidence is thin.

On this page

• How the nine tactics rank
• Tactics 1 and 2: get retrieved
• Why is retrieval not the same as citation?
• Tactics 3 to 5: get cited
• Tactics 6 to 9: slower and smaller levers
• What should you stop doing for AI search?
• Does AI search optimization replace SEO?
• Where AI search optimization goes after the first nine

How the nine tactics rank

The nine tactics rank by effect per hour of effort, starting with the ones that gate everything else. The diagram below scores each on effort and on whether it mainly helps retrieval, citation, or both.

The table shows what each tactic rests on, which matters as much as its rank.

Two caveats apply to everything below. No one outside the engines can see how retrieval and citation are weighted, and Google notes that even a page meeting every requirement is not guaranteed to be indexed or served. And the studies we cite are correlations from one engine’s behavior, so treat them as direction, not dosage.

If you want the full framework behind this ranking, read the complete guide to generative engine optimization. If you want a pass/fail audit instead, use the 40-point GEO checklist. This post does something narrower: it orders the work.

Tactics 1 and 2: get retrieved

The first two tactics are plumbing, and they rank highest because every other tactic fails silently without them.

Tactic 1: open the door to search bots and get indexed. Google says generative AI features use content that is publicly accessible and crawlable, and that a page must be indexed and eligible to show a snippet in Search. For ChatGPT, OpenAI’s crawler documentation says OAI-SearchBot is what shows sites in ChatGPT’s search answers, and that a site blocked from it is excluded from those answers, though it can still appear as a navigational link. OpenAI also says search-related robots.txt changes can take about 24 hours to take effect.

The trap is that people block “AI” in one sweep. OpenAI says GPTBot, which collects content that may be used for training, does not affect search appearance. So you can disallow training and still be searchable. Our robots.txt for AI crawlers post has the file, and should you block AI crawlers covers the decision. Check your CDN rules as well, because a bot blocked at the edge never sees robots.txt.

Effort: an hour. Effect: it decides whether the rest of the list can work.

Tactic 2: make the content render without JavaScript. Google says it can process JavaScript if it is not blocked, but that JavaScript-heavy sites need extra care. Other AI crawlers are not documented to the same depth, so do not assume they behave like Googlebot. The test is cheap: fetch the raw HTML of your key pages and read it. If your pricing, your answer or your service description is not in that response, treat it as invisible until you have proven otherwise. The details are in JavaScript rendering for AI crawlers.

Effort: zero if you already server-render, a project if you do not. That is why it ranks second, not first.

Why is retrieval not the same as citation?

Retrieval means an engine fetched your page as a candidate. Citation means it used and linked your page in the answer. The second is much rarer than the first.

Search Engine Land reported in March 2026 on an AirOps analysis of 548,534 pages retrieved across 15,000 ChatGPT prompts, and only 15% of retrieved pages appeared in final answers. The same report found 55.8% of cited pages ranked in Google’s top 20.

A second AirOps study, covering 16,851 unique queries and 353,799 scraped pages, looked at what separates the survivors. The strongest single pattern was position in ChatGPT’s own retrieval results. The chart below shows it.

This is why tactics 1 and 2 are necessary but not enough. They get you into the pool, and the next three decide where you land in it. The longer explanation is in retrieval vs citation.

Tactics 3 to 5: get cited

These three change what the engine finds when it reads your page, and they are where most of the real gains sit.

Tactic 3: answer first, under the question people actually ask. Put the answer in the first sentence under a heading that matches the query. The AirOps study measured how closely the best-matching heading on a page resembled the query: pages where that similarity was below 0.50 were cited 30.2% of the time, rising to 41.0% at 0.90 or above. That is a correlation, but it fits how retrieval works, since an engine reads a heading before it reads the paragraph under it.

Google’s guidance adds a limit. It says you do not need to chunk content into tiny pieces, and that there is no ideal page length. So write clear sections with an answer on top, and do not slice a good page into fragments. We cover the middle path in content chunking for AI.

Effort: low, because you are rewriting openings, not producing pages.

Tactic 4: add original evidence. This is the highest-effort citation tactic and the one with the best support. Google says it favors a unique point of view and first-hand experience over summaries of existing content. The 2024 research paper GEO: Generative Engine Optimization reports visibility gains of up to 40% in generative engine responses on its benchmark. The authors also found that adding statistics, quotations and cited sources did well, and that keyword stuffing offered little to no improvement.

Treat the 40% as a ceiling on a test setup, not a promise on a live engine. The direction is useful, though: give a model something specific to quote, such as a measured number, a named source or a first-hand observation. If you have none, you cannot add it by rewording. You have to produce it.

Effort: high, because it needs real data, real experience or real sourcing.

Tactic 5: cover the sub-questions the engine will ask. Google describes query fan-out: the system issues related searches to gather more results for a single query. In AirOps’s data, 88.6% of queries produced exactly two fan-out sub-queries. A page that answers the main question and the obvious follow-ups has more ways to be retrieved.

AirOps also found that moderate fan-out coverage (26 to 50%) outperformed exhaustive coverage when the page already matched the main query closely. So add the two or three follow-up questions a buyer would ask, not forty.

Tactics 6 to 9: slower and smaller levers

The last four tactics are worth doing, but none of them will carry a program alone.

Tactic 6: earn real third-party mentions. Mentions on sites an engine already trusts give it a second source for what you say about yourself. Google adds a warning: it says seeking inauthentic mentions is less useful than it seems, because its ranking and spam systems weigh quality. So this is a publicity task, not a placement purchase. The practical version is in digital PR for AI search. It ranks sixth because it is slow and its effect is hard to attribute.

Tactic 7: refresh pages when the facts change. AirOps found pages aged 30 to 89 days had the highest citation rate, at 32.8%. That is a correlation, and it does not tell you that touching old pages causes citations. Update a page when its prices, steps or numbers change, and change the visible content with it. A date bump without a change is the cheapest-looking tactic here and the least honest.

Tactic 8: add JSON-LD. In the AirOps data, 38.5% of pages with JSON-LD were cited against 32.0% without it. Google, however, says structured data is not required for its generative AI features and that no special schema.org markup is needed. Both can be true if schema pages are simply better built overall. Use it for rich results and entity clarity, and read structured data for AI search before expecting more.

Tactic 9: measure with a fixed prompt set. Measurement does not raise your odds, but without a baseline you cannot tell which tactic worked. Run the same 30 to 50 buyer questions each month and record whether you were named, cited and described correctly. Google points to the Generative AI performance report in Search Console for how content shows up in its AI features, and warns against third-party tools that claim access to internal Google metrics. The AI visibility metrics that matter post lays out what to record.

What should you stop doing for AI search?

Stop anything that adds work but does not change what an engine can fetch, read or trust. The diagram below lists the six we see most often, with the source for each verdict.

Three of those need a note. On llms.txt, Google says it does not use such files and that making one for other services is harmless, so it is optional, not harmful; see what is llms.txt. On synonyms, Google says its systems match meaning without exact keywords, so do not rewrite a good page to hit every variant. On volume, Google says more pages do not make a site higher quality, and that many pages made mainly to manipulate rankings or AI responses may violate its scaled content abuse policy.

Does AI search optimization replace SEO?

No. It sits on top of SEO, and the first two tactics are plain technical SEO. Google’s guide states that generative AI features are built on its core ranking and quality systems, and the AirOps data shows most cited pages already rank well on Google.

What is new is the gap between being found and being quoted. Classic SEO ends at the ranking. AI search optimization continues through retrieval and into the answer, which is why tactics 3 to 5 exist. The three terms overlap heavily, and AEO vs GEO vs SEO sorts out the vocabulary.

One more distinction matters for budgets. Tactics 1 to 3 and 7 to 9 are cheap and fast, so do them this month. Tactics 4 to 6 are slow and cost real effort, so sequence them over a quarter, as in the 90-day AI SEO roadmap.

Where AI search optimization goes after the first nine

Once the nine are done, the work becomes an ongoing loop: re-run your prompt set, find the questions where a competitor is cited instead of you, and fix those pages first. The ranking above will also shift, because engines change how they retrieve and select sources without notice.

If you would rather hand that loop to someone, our GEO service covers the technical fixes, the content restructuring and the monthly measurement. Our free AI visibility audit is a smaller first step: it shows which of the nine are already in place on your site and which are missing. The checklists library at /checklists/ has step-by-step lists for the technical items.