200+ AI audits reveal why some industries struggle in AI search

For 20 years, the web has run on a simple trade: publish content that meets a person’s needs, rank in search, earn traffic, then monetize that traffic through products, services, affiliate referrals, or ads.

Zero-click answers and AI search are rewriting that relationship. The new question is whether AI will cite you as a source — and whether that visibility can turn into revenue.

To understand who gets included and who gets routed around, I ran over 200 AI visibility audits across 10 industries.

The pattern was consistent: Most sites are easy to parse, but hard to justify citing. And the industries that rely on discovery traffic the most are often the ones making themselves the hardest to access.

How the audit was conducted

I ran 201 audits using the same rubric and captured an overall AI visibility score, plus four subscores: 

• Freshness.
• Structure.
• Authority and evidence.
• Extractability.

The dataset included 201 audits across 10 industries:

• Coupons.
• Affiliate reviews.
• Travel booking.
• Local directories.
• Personal finance comparison.
• Health information.
• Legal directories.
• Online courses.
• Job boards.
• Recipes.

Note that there was a page type skew — the sample is homepage-heavy (131 homepages, 13 articles, with the remainder a mix of pages). That matters because homepages tend to be marketing-heavy and evidence-light.

I also tracked access failures because “error” results are part of the story. 38 of the 201 audits (18.9%) returned an error, meaning the agent was likely blocked or couldn’t reliably access the content.

An additional eight audits were technically processed but scored 0 due to missing subscores, consistent with partial extraction or app-style rendering that yields little accessible content.

When I summarized score distributions, I focused on the successfully processed audits (163 sites), so “cannot access” didn’t get mixed with “low quality.” I treated error rate by industry as its own signal because it indicated whether AI systems could reliably use a site as a source.

Where industries stand in AI visibility

The table below shows how the industries in the dataset performed in the audits.

What the audits actually revealed

The findings show that most websites aren’t built to be cited consistently. Here are the three numbers that matter.

Access is a bigger problem than most teams think

38 of 201 sites (18.9%) returned an error. In some categories, it was far worse: job boards (40%), legal directories (35%), travel booking (33%), and course marketplaces (30%). In those spaces, a third to nearly half of the market is effectively AI-dark by default.

Legal directories had the highest AI blocking of any industry.

Most sites are stuck in the middle

Across the 163 processed audits:

• Average overall score: 61.6
• Median overall score: 66
• 70.6% landed in “Inconsistent visibility” (60 to 79)
• Only 4.9% reached “Strong foundation” (80 to 94)
• 0% hit “Exceptional” (95 plus)

Translation: Most brands aren’t built to be reliably used and cited.

The gap is proof, not formatting

Median subscores across processed audits:

• Structure: 92
• Extractability: 74
• Authority and evidence: 48
• Freshness: 45

Most pages are easy to parse. Far fewer are easy to justify citing. Two repeated findings explain why:

• “No last modified header detected” showed up 114 times (machine-readable freshness is missing).
• Citations or outbound references appeared only 13 times (machine-readable proof is rare).

That should change how you think about risk. More than losing traffic, the bigger threat is being removed from the consideration set.

Dig deeper: What 4 AI search experiments reveal about attribution and buying decisions

3 ways an industry vanishes from AI search

Industries disappear for three reasons. You can think of them as three failure modes.

1. Access failure: AI can’t reliably reach your content

If agents can’t consistently access your content, the model has less to work with and will either route around you or fill in the gaps from other sources.

What access failure looks like:

• Bot protections, rate limiting, or web application firewall (WAF) rules that treat agents as hostile.
• App-style rendering where meaningful content never arrives in initial HTML.
• Content gated behind prompts, popups, or scripts that don’t resolve cleanly.

Why this causes vanishing:

• If AI systems can’t reliably extract, they can’t reliably cite.
• The user’s intent still gets satisfied — it just gets satisfied by someone else’s crawlable content or a native AI answer.

2. Trust failure: AI can read you, but can’t justify citing you

Trust failure is quieter. The agent can access your page, parse it, and summarize it, but the page doesn’t provide enough proof for the model to confidently cite it as a source.

This was the dominant pattern in the completed audits. In plain language: Your content is readable, but it isn’t defensible.

The clearest proof of this showed up when I compared page types:

• Median authority score on article pages: 76
• Median authority score on homepages: 45

A polished homepage isn’t proof. If you want to be cited for anything beyond your brand name, a typical homepage alone isn’t enough. Evidence usually lives in articles, explainers, data pages, policy pages, and methodology pages.

3. Utility failure: Even if you’re visible, the click may not happen

Utility failure is the most painful. You might get included. You might get cited. But if your value is only information, AI can compress it into an answer, and the user never needs to visit your site.

Visibility determines whether you appear in the conversation. Utility determines whether appearing turns into revenue.

A practical way to think about it:

• If your page answers the question, AI can replace the page.
• If your product or service completes the job, AI still needs you.

Access failure gets you excluded. Trust failure gets you skipped. Utility failure gets you summarized.

Why certain industries show up as vulnerable

Once access, trust, and utility get viewed together, the vulnerable industries stop looking random.

The categories that repeatedly showed high risk in my dataset share three traits:

• Access is inconsistent (blocking and extraction problems).
• The content is easy to compress into a single answer.
• The business has no next step value once the answer is delivered.

That’s why travel booking, job boards, legal directories, and coupon sites clustered as the most exposed categories in this dataset.

The bigger takeaway? Your website can be built in a way that invites exclusion, even if your business is healthy.

Dig deeper: Why every AI search study tells a different story

The point you shouldn’t miss

Some industries will feel this harder than others. A site funded primarily by high-volume informational traffic is more exposed to zero-click behavior. But even in those categories, the path forward is to stop selling information alone. 

The big mistake right now is treating AI search like a ranking update, when it’s an economic update. The audits made two things obvious:

• Many industries are making themselves hard to access, which guarantees the model will route around them.
• Even when the model can read a page, it often can’t justify citing it because proof is missing.

The threat is invisibility. You don’t win by hiding. You win by becoming cite-worthy and by building something the user still needs after the answer is delivered.

Trust plus utility is the new moat. Anything else is just playing from yesterday’s playbook.