How AI Search Is Recommending ABA Therapy Providers: Monthly Trends

Executive Summary

Action Behavior Centers remains the category leader in September 2026, though its valid recommendation coverage fell to 43.4%, down from 54.0% in July and 54.5% in August. The gap to the next provider, Behavioral Innovations, narrowed to 18.8 points as Behavioral Innovations declined to 24.6% coverage from 29.8% in July. The leader's retreat is the sharpest headline of the month, though the move falls within the benchmark's normal range of month-to-month variation for that metric.

Hopebridge and Trumpet Behavioral Health are the category's two significant decliners over the baseline-to-current period. Hopebridge fell 10.6 points from 31.1% in July to 20.5% in September, a significant decline driven primarily by a 17.7-point drop in raw mention presence. Trumpet Behavioral Health dropped 5.4 points from 6.2% to 0.8% over the same span, also significant, with raw presence down 5.8 points to 1.6%.

Helping Hands posted the strongest upward movement, rising from 1.2% coverage in July to 3.3% in September, a 2.1-point gain with top-three rate up 2.7 points to 3.3%. Acorn Health also climbed from 4.3% to 4.9%, though both remain small-count brands where individual observations carry outsized weight.

Each monthly benchmark run begins with the full prompt-surface collection before qualification. July 2026 collected 614 prompt-surface observations (475 unique questions) across the benchmark's defined AI/search surface universe; September 2026 collected 720 (547 unique questions). August 2026 collected 674 (543 unique questions). All prompts in each month mentioned a tracked brand or competitor; 213 were relevant and 401 irrelevant in July, 238 relevant and 436 irrelevant in August, and 246 relevant and 474 irrelevant in September. The brand-level metrics below use the 161 qualified observations from July, 143 from August, and 122 from September that survived 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.

The qualified surface breadth widened again in September, reaching all six canonical AI surface families with at least one qualified observation. Perplexity entered the qualified set alongside ChatGPT, joining Copilot, Gemini, AI Mode, and AI Overviews, which continued to carry qualified observations across the period.

Benchmark-Level Metrics

The qualified observation count contracted from 161 in July to 122 in September even as the raw collection grew, because a larger irrelevant pool reduced the share of prompts that reached the public denominator. August's recommendation-shaped answer share of 43.4% marked the low point of the series before September recovered to 53.3%, while the valid recommendation shortlist share held near half of qualified observations in all three months.

AI Recommendation Trend

The category leader retreated while the competitive middle tightened

Action Behavior Centers' coverage contracted in September, bringing the next tier of providers closer even as no brand displaced it from first place.

No brand exceeded normal month-to-month variation between August and September, yet the baseline-to-current period contains two significant declines in Hopebridge and Trumpet Behavioral Health. The category-level contraction came from the combination of several smaller movements against a shrinking qualified denominator.

What Changed This Month

Action Behavior Centers

Action Behavior Centers' valid recommendation coverage fell 10.6 points from 54.0% in July to 43.4% in September, with the sharper month-over-month drop of 11.1 points coming between August and September. Its raw mention presence declined 14.4 points from 78.3% to 63.9%, even as its top-three rate held comparatively steady at 41.8% versus 42.9% in July.

The brand still appeared in 78 of 122 qualified observations with 53 valid recommendations, including 51 top-three placements and 31 rank-one results. Its average recommended rank improved to 1.57, its best of the three-month series.

The distinction to notice: Action Behavior Centers is being mentioned less often, but when mentioned it is placed at or near the top of the recommendation list more consistently. The data describes this output distribution; it does not establish why the pattern occurred.

Highest-priority diagnostic: Which prompts and surfaces reduced their mentions of Action Behavior Centers, and which provider absorbed those recommendation slots?

Hopebridge

Hopebridge's valid recommendation coverage fell a significant 10.6 points from 31.1% in July to 20.5% in September, with the bulk of the decline occurring in August. Raw mention presence dropped a significant 17.7 points from 49.7% to 32.0%, indicating the brand appeared in AI answers far less often across the three-month period.

Hopebridge recorded 25 valid recommendations in September versus 50 in July, with top-three placements falling from 30 to 20. Despite the overall retreat, its rank-one rate improved slightly from 6.2% to 6.6%, with 8 first-place recommendations in September.

The distinction to notice: Hopebridge's presence in AI answers fell sharply, and its recommendation counts fell roughly in proportion, while its rank-one rate did not decline alongside the broader retreat. Its prior-month movement of 3.0 points up from August's 17.5% suggests the drop may have stabilized.

Highest-priority diagnostic: Which prompt types or surfaces reduced their mentions of Hopebridge most sharply, and which competitor took those recommendation slots?

Trumpet Behavioral Health

Trumpet Behavioral Health's coverage fell a significant 5.4 points from 6.2% in July to 0.8% in September, with a two-month decline streak. Raw mention presence dropped 5.8 points from 7.4% to 1.6%, leaving the brand present in just 2 of 122 qualified observations.

The brand recorded 1 valid recommendation in September with a single top-three placement and no rank-one results, down from 10 valid recommendations in July. Its net sentiment score slipped from 0.9 to 0.5 across the period.

The distinction to notice: Trumpet Behavioral Health declined across both presence and recommendation coverage, and the counts are now so small that a single observation can move its metrics materially.

Highest-priority diagnostic: Which surfaces dropped Trumpet Behavioral Health from their answers, and which providers now occupy the slots it previously held?

Helping Hands and Acorn Health

Helping Hands rose 2.1 points from 1.2% in July to 3.3% in September, the largest upward movement among stable brands. Its top-three rate climbed 2.7 points to 3.3% with 4 top-three placements and 1 rank-one result, up from 1 top-three placement and zero rank-one results in July.

Acorn Health gained 0.6 points from 4.3% to 4.9% coverage, with top-three rate up 0.6 points to 2.5% and raw presence down 0.7 points. Both brands carry small absolute counts: Helping Hands recorded 4 valid recommendations in September and Acorn Health 6.

The distinction to notice: Helping Hands added top-three and rank-one placements it did not have in the baseline month, while Acorn Health improved coverage despite slightly lower presence. Neither movement crossed the threshold applied to significant decliners in this series, and both remain small-count stories.

Highest-priority diagnostic: For Helping Hands, which prompts produced the additional top-three placements, and for Acorn Health, which mentions converted into recommendations?

Buyer-Intent Interpretation

All 122 qualified observations in September 2026 fell into the Brand Recommendation cluster, the same pattern as July and August where all qualified observations were also recommendation-focused. The benchmark therefore measures which provider AI systems recommend when asked directly, and how consistently that recommendation holds across surfaces.

The public benchmark cannot yet answer pricing, value, or head-to-head comparison questions, because no qualified observations fell into those clusters in any month of the series. For providers competing on cost, insurance acceptance, or specific comparative advantages, the current data does not reveal how AI systems characterize those differences.

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 capturing the 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 Index
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• The qualified set (122 observations in September) differs from the raw collection (720 prompts); all percentages reference the qualified set.
• Small counts apply to several brands: Trumpet Behavioral Health (1 valid recommendation), Helping Hands (4), Centria Autism (5), Acorn Health (6), and LEARN Behavioral (6) require caution in interpreting movement.
• Directional analysis identifies changes worth investigating; it does not by itself establish cause.
• The benchmark tests six canonical AI surface families; all six met the qualification bar in September (ChatGPT, Copilot, Gemini, Perplexity, AI Mode, AI Overviews).
• The qualified denominator contracted across the series (161 to 143 to 122), so percentage movements reflect both brand-level changes and the smaller base.

Next Step

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

The aggregate percentages only reveal the surface. Beneath the numbers sit questions the public benchmark cannot answer: which high-intent prompts a brand wins or loses, which competitor takes the recommendation when a brand is not chosen, what attributes AI associates with each provider, and which external sources shape those answers. For a category like ABA therapy providers, where parents are making high-stakes care decisions, those details determine whether a recommendation converts into an inquiry.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. The benchmark shows where attention is warranted; the audit explains why and what to do about it.

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