Life Insurance Companies: AI Visibility Market Discovery Index

Benchmark Summary

Ethos led the Life Insurance Companies AI Visibility Market Discovery Index in October 2026 with a valid recommendation coverage of 51.9%, ahead of Ladder at 50.3% by 1.6 percentage points. No brand recorded a coverage increase beyond normal month-to-month variation in October 2026; the two largest movements of the month were both increases within that range, with Bestow up 2.8 points from September 2026 and Ethos up 2.3 points from September 2026. The largest coverage decline of the month was Policygenius, down 5.4 points from September 2026, which fell within normal variation for the month. Across the full July-to-October 2026 series, four brands declined beyond normal variation from the July 2026 baseline: Policygenius from 58.2% to 28.5%, Ethos from 73.8% to 51.9%, Ladder from 69.5% to 50.3%, and Bestow from 17.2% to 11.2%. Policygenius declined in each of the three months since July 2026.

The benchmark began with 800 prompt-surface observations in each month and produced 419 qualified observations in July 2026 and 376 in October 2026 after qualification.

Current Benchmark at a Glance

Qualified surface breadth counts the canonical AI/search surface families with at least one qualified observation in the month. The six canonical families are ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. September 2026, the intermediate month, recorded a recommendation-shaped answer share of 45.4% and a valid recommendation shortlist share of 57.2%.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Life Insurance Companies

Research Scope and Qualification

Brand-level percentages in this report use qualified benchmark observations as the public denominator, not the raw collection universe.

Brand-level percentages use the qualified observations as the public denominator, not the raw collection. See the AI Visibility Market Discovery Methodology.

Current Brand Standings

Questions This Section Answers

• Which life insurance brands lead on valid recommendation coverage in October 2026?
• How do presence, top-three, and rank-one rates differ across the tracked brands?
• What do these standings reveal about Everyday Life Insurance's position?

How to Read the Standings

• Presence rate: share of qualified observations where the brand appears in the AI response.
• Valid recommendation coverage: share of qualified observations where the brand appears as a valid recommendation, including a mention in context that meets the recommendation criteria.
• Top-three rate: share of qualified observations where the brand appears among the top three recommended options.
• Rank-one rate: share of qualified observations where the brand is the first-ranked recommendation.
• Net sentiment: positive sentiment share minus negative sentiment share across mentions.

For formulas and denominator rules, see AI Visibility Market Discovery Metric Definitions.

Everyday Life Insurance: Company Position

Questions This Section Answers

• Where does Everyday Life Insurance stand on presence and recommendation coverage?
• What does the gap between Everyday Life Insurance and the category leader indicate?

Everyday Life Insurance recorded a 1.3% presence rate in October 2026, alongside 0.0% valid recommendation coverage, 0.0% top-three rate, 0.0% rank-one rate, and a net sentiment of 0.0. Across the July-to-October 2026 series, its recommendation coverage moved from 0.2% to 0.0%, a decline of 0.2 points. The gap is absence from the qualified observation set, not failed conversion.

Ethos records 51.9% valid recommendation coverage, while Everyday Life Insurance stands at 0.0%. The more important issue is what that gap means for Everyday Life Insurance's recommendation position: with presence at only 1.3% against Ethos's 84.8%, the shortfall is not a conversion problem on top of healthy visibility — the brand is largely absent from the qualified observation set itself, and the little presence it has is not translating into any recommendation, top-three placement, or first-choice outcome. This is a material gap on the category's primary commercial metric, not a narrow or incidental one.

Highest-priority diagnostic: Why does Everyday Life Insurance generate almost no presence (1.3%) or valid recommendation coverage (0.0%) across the six canonical AI surfaces, while the category leader, Ethos, achieves 84.8% presence and 51.9% recommendation coverage over the same qualified observation set?

Recommendation Coverage Movement

Questions This Section Answers

• Which brands declined beyond normal variation since the July 2026 baseline?
• What does Policygenius's month-over-month decline pattern show?
• Is Ethos's movement since the baseline a meaningful decline or normal variation?

Largest Increase: Quotacy

Quotacy recorded the largest increase of the series, moving from 1.7% in July 2026 to 2.1% in October 2026, an increase of 0.4 points that falls within normal month-to-month variation. Its recommendation coverage also rose 0.3 points from September 2026, again within normal variation, on only 8 qualified recommendations in the current month.

Largest Decline: Policygenius

Policygenius recorded the largest coverage decline of the series, moving from 58.2% in July 2026 to 28.5% in October 2026, a drop of 29.7 percentage points beyond normal month-to-month variation. Policygenius declined in each of the three months since July 2026. Its most recent move, from 33.9% in September 2026 to 28.5% in October 2026, was a decline of 5.4 points that falls within normal variation. Its presence rate fell from 78.5% in July 2026 to 62.5% in October 2026, and its top-three rate dropped from 22.2% to 18.9% across the same period. Three consecutive monthly declines point to a sustained loss of recommendation position.

Category Leader: Ethos

Ethos led the category with 51.9% valid recommendation coverage in October 2026, ahead of Ladder at 50.3% and Policygenius at 28.5%. Although Ethos remains the leader, its coverage declined from 73.8% in July 2026 to 51.9% in October 2026, a drop of 21.9 percentage points beyond normal month-to-month variation. It moved up 2.3 points from September 2026, within normal variation. Its margin over Ladder stands at just 1.6 points.

Recommendation Placement Snapshot

Questions This Section Answers

• How do top-three and rank-one rates differ between Ethos, Ladder, and Policygenius?
• Can a lower-coverage brand still achieve a high first-position rate?

Coverage alone does not show how prominently a brand is recommended. Placement rates reveal whether a brand appears at the top of the list or deeper in the response.

Ethos and Ladder held near-identical top-three rates in October 2026, at 37.5% and 37.0%, but Policygenius carried a rank-one rate of 10.9% despite having considerably lower valid recommendation coverage than either leader. Similar coverage levels can still hide very different first-position rates, and the reverse is also true: a lower-coverage brand can hold a first-position rate close to the leaders'.

Buyer-Intent Distribution

The qualified observations in October 2026 fell into the Brand Recommendation class.

The current public series measures brand recommendation discovery only; pricing, value, and head-to-head comparison questions have no public signal in this data.

Historical Measurement Record

Questions This Section Answers

• Has the category leader changed across the July-to-October 2026 series?
• What do the monthly measurements show about coverage movement over time?

This is an evergreen benchmark URL. New measurements are added to the same report.

The leader has not changed, but the leader's own coverage has fallen sharply and continues to erode.

Evidence and Source Layer

The benchmark is built from prompt-level observations that retain the query, AI/search surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources. Source presence is evidence about the information environment, not automatic proof that the source caused the recommendation.

Scope Boundaries

This public benchmark does not measure:

• Market share or sales attribution
• Every possible AI response or AI surface
• Organic-search ranking positions
• Social media mention volume
• Private or sponsored channels such as paid placements and internal tools
• Causality from a metric movement alone

Top 10 Cited Domains

Questions This Section Answers

• Which domains are most cited in AI responses about life insurance brands?
• How concentrated are citations across the top sources?
• Which life insurance brands' own domains appear among the top cited sources?

The benchmark observed 6,169 citations across 1,765 unique domains in October 2026.

Citations are broadly distributed rather than concentrated, with the largest single source accounting for only 4.5% of all citations and no single domain dominating. Two tracked brands' own domains appear in the top 10, with ethos.com at rank 4 and policygenius.com at rank 5, each cited across all six canonical AI surface families. Beyond those, the sources shaping AI recommendations in this vertical are a mix of consumer review and comparison sites, search and social platforms, general news outlets, and established insurer sites.

About This Benchmark

The LLM Authority Index AI Visibility Market Discovery Index is a neutral industry benchmark that tracks how AI search and chat surfaces discover, mention, and recommend brands. It measures presence, recommendation coverage, placement, and sentiment across six canonical AI surface families. New measurements are added to the same evergreen report each month.

Research links:

• AI Visibility Market Discovery Methodology
• AI Visibility Market Discovery Metric Definitions
• AI Visibility Market Discovery Research Standards
• Modeled AI Visibility Authority Value

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The public industry benchmark shows category-level standings. A company-level Authority Index can go deeper. The public percentage cannot identify the prompts, competitors, or sources causing the result.

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