Zero-click search: 8 industries ranked by AI visibility loss

Rand Fishkin has been saying this for years: zero-click search is not an AI problem. It's a Google problem that started around 2012 when featured snippets, knowledge panels, and direct answers began absorbing intent that used to generate clicks.

His point, made recently in a Search Engine Land retrospective, is worth sitting with. Because if you've been telling your clients that AI Overviews are the beginning of the end, you've been giving them the wrong timeline. The erosion has been running for over a decade.

What AI actually did was compress that erosion into a much shorter window and spread it across many more query types simultaneously.

For brands, this distinction matters because the fix is different depending on how far along the decay already is. Some industries have been adapting to zero-click conditions since 2015. Others walked into an AI wall in 2024 having done nothing.

Here's how eight industries stack up, ranked by their current exposure to AI visibility loss.

Ranking methodology

Each industry is scored on four criteria. These are not arbitrary. They reflect what I look at when running AI visibility audits for agency clients.

Criterion	What it measures	Weight
Query absorption rate	Share of high-volume queries now answered directly in AI/SERP	35%
Brand differentiation in AI answers	How often specific brands are named vs. generic responses	25%
Content structure for AI citation	Industry content's suitability for LLM extraction	25%
Historical zero-click exposure	Years of pre-AI featured snippet and knowledge panel pressure	15%

Scores are informed by publicly available click-rate data from SparkToro's research, BrightEdge AI search reports, and category-level analysis from Moz. Where direct data isn't available, estimates are flagged.

#1: Health and medical information

Medical queries have been zero-click territory since Google introduced health knowledge panels and symptom cards in 2016. By the time AI Overviews launched, the click erosion in informational health queries was already estimated at 60-70% for top-of-funnel terms.

AI has made this worse in one specific way: it now handles nuanced symptom questions that previously required clicking through to WebMD or Mayo Clinic. Brands like WebMD and Healthline have lost meaningful organic traffic share, while neither appears consistently in AI-generated health answers without explicit brand queries.

Strength: High-trust brands with E-E-A-T signals still get cited in AI answers for complex clinical questions. Weakness: Informational query absorption is near-total. Generic symptom and condition queries almost never produce clicks.

AI visibility loss score: 91%

#2: Finance and personal finance

Calculator queries, interest rate lookups, tax bracket questions, and basic investment definitions have been answered in-SERP since 2014. BrightEdge has reported that financial services sees some of the highest AI Overview trigger rates of any vertical.

Brands like NerdWallet and Bankrate built their entire model on capturing informational finance traffic. That model is under severe pressure. However, brands with strong review content and comparison tools are still being cited by Perplexity and ChatGPT when users ask for product recommendations.

Strength: Comparison and product-recommendation queries still drive brand citations in AI engines. Weakness: Any query with a calculable answer is now fully absorbed. No click required.

AI visibility loss score: 87%

#3: Travel and hospitality

This one surprised clients when I first showed them the data. Travel feels like a high-intent, click-heavy vertical. But informational travel queries (best time to visit, visa requirements, average costs) have been zero-click since Google's travel carousels and knowledge panels expanded in 2018.

AI has added another layer. Perplexity and ChatGPT now give detailed itineraries, packing lists, and cost breakdowns without sending users to travel blogs. Booking.com and Expedia still appear in transactional queries, but the awareness and consideration phases are almost entirely absorbed.

Strength: Transactional queries with booking intent still generate clicks and brand citations. Weakness: The top-of-funnel, which used to feed loyalty and brand recall, is effectively gone.

AI visibility loss score: 79%

#4: Legal information

Legal is interesting because AI engines are cautious here. There's been a measurable pull-back from confident legal advice in AI-generated answers, which creates a small window of opportunity for law firm brands.

But general legal information queries (statute of limitations, how to file a small claims case, landlord rights) are increasingly answered in-SERP and in AI. Brands like LegalZoom and Avvo get cited in some AI answers, but inconsistently. Smaller firms are nearly invisible.

Strength: AI caution around legal advice means complex queries often redirect to professionals. Weakness: Informational legal queries are absorbed. Brand differentiation within AI answers is low.

AI visibility loss score: 72%

#5: Software and SaaS

SaaS brands are in a complicated position. AI engines love recommending software. ChatGPT, Perplexity, and Gemini regularly produce "best tools for X" lists. The brands that appear in those lists get meaningful referral traffic. The ones that don't are invisible in the new discovery layer.

This is where winek.ai is most useful practically. SaaS brands can measure exactly how often they appear in AI-generated tool comparisons versus competitors. The visibility gap between brands that have optimized for AI citation and those that haven't is significant, often 40 to 60 percentage points in the same category.

Tools like HubSpot, Notion, and Slack appear frequently. Mid-market SaaS brands with strong feature sets but weak AI-visible content structures are consistently missing from AI answers.

Strength: AI engines actively recommend tools, creating real discovery opportunities. Weakness: The distribution is winner-takes-most. Top-cited brands dominate; everyone else is absent.

AI visibility loss score: 58% (with high variance by brand)

#6: Retail and e-commerce

Retail is more resilient than most people expect. Product queries with commercial intent still generate clicks because AI engines generally avoid making specific product purchase decisions for users. Google's own research shows Shopping ads and product carousels remain click-generative even within AI Mode.

Where retail loses is in informational pre-purchase queries: "what size should I buy," "is this material good for cold weather," "how does X brand compare to Y brand." These are now frequently answered in AI without a click.

Brands like Nike and Patagonia appear in AI answers for brand-specific queries, but generic category queries produce generic AI answers with minimal brand naming.

Strength: Transactional product queries still generate clicks. Brand queries still surface brand content. Weakness: Pre-purchase informational queries are absorbed. Brand building at the consideration stage is harder.

AI visibility loss score: 51%

#7: B2B technology and enterprise software

Enterprise B2B is one of the least-affected categories, for a specific reason: the queries are complex, the buyer journey is long, and AI engines hedge heavily on enterprise recommendations. You won't get ChatGPT confidently recommending a specific ERP system.

What AI does affect here is the early-stage research phase. Analysts at enterprise companies use Perplexity and ChatGPT to build initial vendor shortlists. Brands that appear in those AI-generated shortlists get into consideration. Brands that don't are filtered out before a human even visits a website. Gartner's research on buyer behavior underscores how much of enterprise buying now happens in dark funnel channels before any vendor knows a deal is in motion.

Strength: Complex queries resist AI absorption. Brand authority still matters. Weakness: Early-stage vendor shortlisting now happens inside AI engines. Invisible brands lose before the first call.

AI visibility loss score: 38%

#8: Local services

Local is the most resilient category. Queries like "plumber near me" or "best dentist in Austin" produce Google Maps results, not AI Overviews. The transactional and geographic specificity of local queries makes them difficult for AI to absorb fully.

This isn't zero risk. AI does answer "how to find a good plumber" or "what to ask a contractor before hiring." But the core local discovery mechanism still drives clicks.

Strength: Geographic and transactional specificity protects local queries from AI absorption. Weakness: Informational pre-hire queries are being absorbed, affecting top-of-funnel brand awareness.

AI visibility loss score: 29%

Summary scorecard

Industry	Query absorption	Brand differentiation	Content structure	Historical exposure	Overall score	Rating
Health and medical	95%	40%	55%	90%	91%	★★★★★
Finance	90%	50%	60%	85%	87%	★★★★★
Travel	80%	55%	65%	75%	79%	★★★★☆
Legal	75%	45%	60%	70%	72%	★★★★☆
SaaS	55%	70%	65%	45%	58%	★★★☆☆
Retail	50%	65%	60%	50%	51%	★★★☆☆
B2B tech	35%	75%	55%	30%	38%	★★☆☆☆
Local services	25%	80%	50%	25%	29%	★★☆☆☆

The pattern is clear. Industries with high concentrations of informational queries and weak brand differentiation in AI answers are the most exposed. Industries where queries require local, transactional, or deeply complex resolution are more protected, for now.

Fishkin's core argument holds: the problem predates AI. But AI has changed the rate of change. Industries that had a decade to adapt to featured snippets now have months to adapt to AI Overviews and conversational search engines. That's a fundamentally different planning problem, and most brand teams aren't treating it that way yet.

Frequently asked questions

Q: What is zero-click search and when did it start?

A: Zero-click search refers to search sessions where a user gets their answer directly on the results page without clicking through to any website. According to Rand Fishkin and SparkToro's research, this behavior began accelerating around 2012 to 2015 as Google expanded featured snippets, knowledge panels, and direct answer boxes. AI Overviews and conversational AI engines have intensified the trend but did not originate it.

Q: Which industries are most vulnerable to AI visibility loss?

A: Health, finance, and travel are the most exposed industries based on query absorption rates. These verticals have high concentrations of informational queries where AI can provide a complete answer without requiring a click. Brands in these categories have been losing informational traffic since the mid-2010s and are now facing a second wave of absorption from AI-generated answers.

Q: Can SaaS brands benefit from AI search rather than just losing from it?

A: Yes, SaaS is one of the few categories where AI search can actively drive discovery rather than purely absorb traffic. AI engines like ChatGPT and Perplexity regularly recommend specific software tools in response to user queries. Brands that appear in those AI-generated recommendation lists gain real visibility with high-intent buyers. The challenge is that appearance in these lists is not random and requires deliberate GEO optimization, including structured content, third-party citations, and consistent entity presence.

Q: How do you measure brand visibility in AI search engines?

A: Brand visibility in AI search is measured by tracking how frequently a brand is named in AI-generated responses across engines like ChatGPT, Perplexity, Gemini, Claude, Grok, and DeepSeek for relevant queries. Tools like winek.ai automate this measurement, allowing brands to benchmark their AI citation rate against competitors and track changes over time. This is distinct from traditional SEO rank tracking, which only measures position in link-based results pages.