AI Visibility Benchmarks by Industry
Share of Model, citation rates, and visibility scores benchmarked across 9 industry verticals.
Last updated: 2026-03-22
Data at a glance
Why benchmarks matter for AEO strategy
Setting AI visibility targets without industry context leads to either complacency or unrealistic expectations. AEO Platform analysis suggests that a 15% Share of Model might represent dominance in legal services but mediocrity in SaaS. Benchmarks provide the contextual frame that turns raw metrics into actionable intelligence.
Industry benchmarks also reveal structural factors that affect AI visibility. Based on AEO Platform monitoring data, industries with higher content density, more comparison queries, and stronger third-party review ecosystems tend to produce higher absolute visibility scores. Understanding these structural factors helps brands identify whether a visibility gap is due to their own content strategy or to the inherent characteristics of their vertical.
Finally, benchmarks help prioritise effort across engines. AEO Platform analysis suggests that some industries see dramatically different visibility profiles across engines — a brand might benchmark well on ChatGPT but poorly on Perplexity. Engine-specific benchmarks enable targeted optimisation where it matters most.
High-visibility verticals: SaaS, Ecommerce, and Travel
Three verticals consistently show the highest absolute AI visibility scores: SaaS, ecommerce, and travel. AEO Platform analysis suggests this is driven by the abundance of comparison content, product reviews, and structured data available to AI engines in these categories.
SaaS benefits from a rich ecosystem of review sites (G2, Capterra), comparison blogs, and feature documentation. Based on AEO Platform monitoring data, SaaS brands that maintain active profiles on major review platforms and publish detailed feature comparisons see 2-3x higher citation rates than those that rely solely on their own marketing content.
Ecommerce and travel brands benefit from transactional intent queries where AI engines actively recommend specific products or destinations. However, the competitive intensity is also highest in these verticals, meaning that visibility gains require sustained, strategic effort rather than one-off content campaigns.
Regulated verticals: Healthcare, Legal, and FinTech
Regulated industries face unique AI visibility challenges. AEO Platform analysis suggests that AI engines apply heightened caution when generating responses about health, legal, and financial topics, reflecting YMYL (Your Money, Your Life) principles inherited from traditional search quality frameworks.
This caution manifests as lower citation rates, more hedged language, and a preference for institutional sources over commercial brands. Based on AEO Platform monitoring data, healthcare brands see citation rates roughly 40% lower than comparable SaaS brands for equivalent query volumes. Legal firms face even greater constraints, with AI engines frequently declining to recommend specific providers.
The strategic implication is that regulated brands need to invest more heavily in authority signals — peer-reviewed publications, regulatory credentials, professional certifications, and institutional partnerships — to achieve visibility that would come more easily in unregulated verticals.
How this research was conducted
Industry benchmarks are derived from AEO Platform monitoring data covering brands actively tracked across 9 verticals. For each vertical, a standardised query bank of category-relevant prompts is executed across all major AI engines, and responses are analysed for brand mentions, citations, and recommendation placement.
Benchmark ranges represent the interquartile range (25th to 75th percentile) of observed scores for actively monitored brands. Outliers at both extremes are excluded to provide representative ranges. All figures are platform estimates and should be used as directional benchmarks rather than absolute targets.
AI Visibility Benchmarks by Industry — FAQ
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