Case Studies

Case studies from LAI.

Explore AI Visibility, the Visibility Trap (SOV vs. recommendation), Citation Architecture, and Pricing AI Search, then open each study for the full analysis.

Library

Published case studies

Case Study

The AI Platform Split: Why a Brand Can Be Visible Across AI Systems but Still Lose Recommendation Power

See why brands can appear across AI systems but still lose recommendation power when platform-specific trust signals differ.

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Case Study

The Brand Alternative Leakage Study: When AI Turns “[Brand] Alternatives” Searches Into Competitor Recommendations

See how AI systems turn brand alternative searches into competitor recommendations, creating leakage from branded demand.

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Case Study

The Thin-Data Warning: When a Public AI Snapshot Is Not Enough to Name a Category Winner

Learn why a public AI snapshot may be too thin to name a category winner without deeper prompt, source, and evidence analysis.

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Case Study

The AI Shortlist Concentration Study: How AI Systems Compress Crowded Markets Into a Few Default Brands

See how AI systems compress crowded insurance markets into a few default brands across pet, travel, and dental insurance categories.

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Case Study

The AI Trust Layer: How AI Systems Decide Which High-Risk Brands Are Safe Enough to Recommend

See how AI systems assess trust, risk, legitimacy, and source validation before recommending brands in high-risk financial categories.

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Case Study

The Citation Architecture Gap: Why AI Systems Trust the Source Layer Before They Recommend the Brand

Learn how AI systems use source layers, citations, and third-party evidence to decide whether brands become recommendation-eligible.

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Case Study

The AI Pricing Gate: How Cost Prompts Decide Whether AI Systems Recommend, Exclude, or Reframe a Brand

See how cost, fee, rate, and affordability prompts decide whether AI systems recommend, exclude, or reframe brands.

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Case Study

The Off-Intent Visibility Trap: How Experian AutoCheck Appeared in AI Credit Monitoring Search Without Winning the Credit Monitoring Job

See how Experian AutoCheck appeared in AI credit monitoring search through adjacent vehicle-history intent without winning recommendation capture.

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Case Study

The AI Marketplace Displacement Study: When AI Systems Use Marketplaces as Evidence but Recommend Providers Instead

See how AI systems use marketplace sites as evidence while recommending individual providers instead of the marketplaces themselves.

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Case Study

The Visibility Trap: How AI SoV Made a Brand Look Like It Was Winning While AI Was Sending Buyers Elsewhere

Life Alert appeared in 55% of AI pricing queries but captured 0% recommendations. Learn why visibility in AI search didn’t translate into buyer selection.

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Case Study

Life Alert Pricing in AI Search: The Biggest Demand Cluster, Zero Recommendation Capture

See why Life Alert had 55.71% pricing-prompt presence but 0% AI recommendation share across 210 prompts and 1.1M modeled queries.

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Case Study

Life Alert in AI Search: Visible, but Not Recommendation-Qualified

See how Life Alert reached 51.6% AI presence but 0% recommendation share across 1,026 prompts, exposing the gap between visibility and buyer choice.

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Case Study

Life Alert's Citation Architecture in AI Search: Why Visibility Did Not Become Recommendation

April 2026 analysis of Life Alert across 1,026 prompts, 10 high-intent clusters, and 6 AI platforms. The core finding: third-party editorial and trust source...

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