How AI Search Is Recommending DNA Testing Kits: Monthly Trends

Executive Summary

AncestryDNA remains the category leader in September 2026 with valid recommendation coverage of 73.3%, a lead of 8.2 points over second-place 23andMe at 65.1%. AncestryDNA's position is stable, having recovered 1.0 point from August's 72.3%, while 23andMe continues a two-month decline that has now become significant. MyHeritage DNA (61.4%) and FamilyTreeDNA (58.8%) complete the upper tier, with the gap between MyHeritage DNA's third-place position and FamilyTreeDNA's fourth-place position narrowing to 2.6 points.

The largest riser this month was Living DNA, up 1.5 points to 16.3% coverage, though this does not erase its significant decline from July's 21.6%. The largest single-month decline belonged to Nebula Genomics, down 1.8 points to 20.0%. Neither move was large enough to break the normal range of month-to-month variation, making this a quiet month against the immediately prior month. The most consequential category-level story remains the set of three significant decliners measured from baseline: 23andMe, Living DNA, and Nebula Genomics.

Across the full July-to-September series, the category shows a widening competitive structure. AncestryDNA has held the leadership position in every month, but the distance between the second tier and the mid-tier has grown, with MyHeritage DNA's lead over Nebula Genomics widening from 34.5 points in July to 41.4 points in September.

Each monthly run begins with 800 prompt-surface observations (399 unique questions in July, 448 in August, 455 in September) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor in each month; 799 were relevant and 1 irrelevant in July, all 800 were relevant in August, and 796 were relevant with 4 irrelevant in September. The public metrics use the 594 qualified observations in July, 607 in August, and 614 in September that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

August's funnel sat between these points: 800 total prompts, 448 unique questions, 800 brand mentions, 800 relevant prompts, 0 irrelevant prompts, and 607 qualified observations. The qualified benchmark observation count is the denominator for every brand-level metric below.

Benchmark-Level Metrics

The recommendation-shaped answer share dipped to 36.1% in August before recovering to 40.1% in September, and the valid recommendation shortlist share followed a similar pattern, falling to 69.5% in August before rising to 70.8%. Both remain below their July levels, indicating a persistent shift in the mix of AI responses toward fewer recommendation-style answers.

AI Recommendation Trend

A Stable Leader With a Widening Second-Tier Gap

Movement in September stayed within the normal range of month-to-month variation for every brand when measured against the prior month. The category-level changes visible across the July-to-September window come from the combination of several sustained movements, with three brands, 23andMe, Living DNA, and Nebula Genomics, each exceeding normal variation over the full series.

What Changed This Month

23andMe

23andMe's valid recommendation coverage stands at 65.1% in September, down 5.9 points from July's 71.0%, a significant decline over the three-month series. The brand's valid recommendation count moved from 422 in July to 400 in September across a qualified set that grew from 594 to 614 observations.

The decline is visible across placement measures. 23andMe's top-3 rate fell from 67.5% in July to 58.1% in September, a drop of 9.4 points, while its rank-one rate fell from 3.0% to 1.3%. The brand's rank-one count dropped from 18 placements in July to 8 in September, and top-3 placements fell from 401 to 357. Its raw mention presence also slipped from 98.0% to 95.6%, a small decline.

23andMe remains highly visible, present in 95.6% of September responses, but is being recommended less often and placed lower. The movement reflects a weakening in recommendation outcomes rather than a loss of presence.

Highest-priority diagnostic: Which prompt themes in September shifted 23andMe from top-3 placements to lower positions, and which brand took those slots?

Living DNA

Living DNA's valid recommendation coverage is 16.3% in September, down 5.3 points from July's 21.6%, a significant decline across the series. The brand's valid recommendation count fell from 128 in July to 100 in September.

The sharpest single-month drop occurred in August, when Living DNA fell 6.8 points to 14.8%, with its rank-one placements falling to 0. September brought a partial recovery of 1.5 points, and the brand regained a single rank-one placement. Its top-3 rate of 1.9% in September remains well below July's 4.5%, with top-3 placements at 12 versus July's 27.

Living DNA's recovery in September was modest and did not restore its July position. The brand remains visible, present in 26.2% of September responses, but its recommendation placement has not returned to prior levels.

Highest-priority diagnostic: Which prompts began returning Living DNA to top-3 placements in September, and which surfaces still omit it?

Nebula Genomics

Nebula Genomics' valid recommendation coverage is 20.0% in September, down 7.3 points from July's 27.3%, the largest significant decline in the category. The brand's valid recommendation count fell from 162 in July to 123 in September.

The decline is broad-based. Raw mention presence fell from 30.3% to 24.4%, and the top-3 rate fell from 9.8% to 6.5%. Top-3 placements declined from 58 to 40. Unlike Living DNA, Nebula Genomics held its rank-one placements, with 8 in September matching its August count and exceeding July's 5.

Nebula Genomics' rank-one rate actually rose 0.5 points over the series to 1.3%, even as its overall coverage and top-3 presence fell. The brand is holding its best placements while losing mid-list recommendation presence.

Highest-priority diagnostic: Which surfaces and question types account for Nebula Genomics' reduced top-3 presence across the three-month series?

Buyer-Intent Interpretation

Across July, August, and September 2026, all qualified observations fell into the Brand Recommendation cluster. The public benchmark measured recommendation-shaped answers and valid recommendation shortlists, but it captured no qualified observations in the Pricing & Value or Multi-Brand Comparison clusters. The public metrics therefore answer the "which brand" question well, but they cannot yet speak to how AI positions these brands on price, value, or direct head-to-head comparison.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Small-count movement: brands with fewer than 10 valid recommendations (tellmeGen, CRI Genetics, Health Nucleus) can move meaningfully with a change of just a few prompts; treat their percentage shifts with caution.
• Qualified denominator: all brand-level percentages are calculated within the qualified set of 614 observations in September, not the 800 raw prompts collected.
• Directional analysis: month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

Beneath the aggregate percentages sit questions the public benchmark cannot answer: which high-intent prompts a brand wins, which competitor takes the recommendation when a brand loses, what attributes AI associates with each option, and which external sources shape those answers. The significant baseline declines at 23andMe, Living DNA, and Nebula Genomics, for example, raise specific questions about which prompts and surfaces drove those shifts across the three-month series.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It turns the benchmark's "what changed" into an actionable "why and what next."

Request an AI visibility audit