How AI Search Is Recommending ABA Therapy Providers: Monthly Trends

Executive Summary

Action Behavior Centers remains the clear category leader in AI recommendation coverage, holding steady at 54.5% in August 2026, up slightly from 54.0% in July 2026. The gap to the next closest provider, Behavioral Innovations, widened to 20.2 points, as Behavioral Innovations rose to 34.3% coverage from 29.8% in July. This consolidates Action Behavior Centers' dominant position at the top of the category for a second consecutive month.

The category's most significant movement this month was Hopebridge's decline. Its valid recommendation coverage fell 13.6 points, from 31.1% in July to 17.5% in August, a significant drop that moved it from the second-most-recommended provider to third. This retreat stood out in an otherwise stable month, where most other brands moved within normal month-to-month variation.

The sharpest upward mover was Behavioral Innovations, which gained 4.5 points of coverage, from 29.8% to 34.3%, alongside a 6.1-point rise in top-three recommendation rate to 32.2%. LEARN Behavioral also improved its rank-one rate from 0.0% to 1.4%, though its overall coverage slipped 2.5 points to 5.6%.

The category as a whole saw meaningful repositioning beneath a stable leader. While Action Behavior Centers held its position, several mid-tier brands shifted, with Hopebridge's significant drop and Behavioral Innovations' rise reshaping the competitive middle of the market.

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; August 2026 collected 674 (543 unique questions). All prompts in both months mentioned a tracked brand or competitor; 213 were relevant and 401 were irrelevant in July, versus 238 relevant and 436 irrelevant in August. The brand-level metrics below use the 161 qualified observations from July and 143 from August 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 also widened this month, growing the universe of AI/search families with at least one qualified observation from four in July to five in August, with ChatGPT entering the qualified set alongside Copilot, Gemini, AI Mode, and AI Overviews.

Benchmark-Level Metrics

The reduction in qualified observations from 161 to 143, combined with the shift in answer types toward more factual answers and ranked lists, contributed to the lower recommendation-shaped answer share. The valid recommendation shortlist share rose, indicating that when recommendations were given, they were more likely to be substantive shortlists rather than passing mentions.

AI Recommendation Trend

Mid-tier repositioning reshapes the competitive order behind a stable leader

Action Behavior Centers maintained its commanding lead, with Behavioral Innovations solidifying second place and Hopebridge dropping from second to third in a single month.

The category movement came from a combination of one significant decline and several smaller shifts. Hopebridge's 13.6-point drop exceeded normal variation, while the moves of Behavioral Innovations, BlueSprig Pediatrics, and others stayed within expected bounds.

What Changed This Month

Hopebridge

Hopebridge's valid recommendation coverage fell 13.6 points, from 31.1% in July to 17.5% in August, a significant decline and the largest movement in the category this month. Its raw mention presence dropped even more sharply, down 23.1 points from 49.7% to 26.6%, indicating the brand appeared in AI answers far less often.

The number of valid recommendations fell from 50 to 25, with top-three placements dropping from 30 to 20. Despite the overall retreat, Hopebridge's rank-one rate actually improved slightly, rising from 6.2% to 7.0%, with 10 first-place recommendations in August versus 10 in July.

The distinction to notice: Hopebridge was mentioned less often but retained its share of top recommendations when it did appear. This suggests the decline was driven more by reduced presence in AI answers than by a fall in recommendation quality.

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

Behavioral Innovations

Behavioral Innovations gained 4.5 points of valid recommendation coverage, rising from 29.8% in July to 34.3% in August, the largest upward move among stable brands. Its top-three recommendation rate climbed 6.1 points to 32.2%, with 46 top-three placements in August versus 42 in July.

Raw mention presence also rose, from 42.2% to 44.8%, with 64 of 143 qualified observations mentioning the brand. Its rank-one rate dipped slightly, down 1.8 points to 6.3%, with 9 first-place recommendations versus 13 in July.

The distinction: Behavioral Innovations strengthened its overall recommendation footprint and top-three share even as its rank-one count fell. This suggests deeper, more consistent inclusion in shortlists rather than a higher share of single best-answer placements.

Highest-priority diagnostic: Which surfaces show the largest gain in Behavioral Innovations mentions, and what changed in the prompts where it moved into top-three position?

Action Behavior Centers

Action Behavior Centers held its leadership position with 54.5% coverage in August, up from 54.0% in July, a small and non-significant gain. Its top-three rate rose 9.5 points to 52.4%, with 75 top-three placements, while rank-one rate reached 32.2% with 46 first-place recommendations.

Raw mention presence declined 6.3 points to 72.0%, though the brand still appeared in 103 of 143 qualified observations. The divergence between lower presence and higher top-three and rank-one rates is notable.

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

Highest-priority diagnostic: Which prompts still do not mention Action Behavior Centers, and which competitor appears in its place?

LEARN Behavioral and Trumpet Behavioral Health

LEARN Behavioral's coverage slipped 2.5 points to 5.6%, yet its rank-one rate rose from 0.0% to 1.4%, with 2 first-place recommendations in August. Raw mention presence actually improved, up 1.6 points to 19.6%, with 28 mentions.

Trumpet Behavioral Health declined 4.1 points to 2.1% coverage, with raw mention presence down 4.6 points to 2.8%. Its valid recommendation count fell from 10 to 3.

The distinction: LEARN Behavioral shows a split between rising presence and falling recommendation coverage, while Trumpet Behavioral Health declined across both measures. Both remain small-count brands where individual observations carry outsized weight.

Highest-priority diagnostic: For LEARN Behavioral, which mentions did not convert into recommendations, and for Trumpet Behavioral Health, which surfaces reduced their mentions?

Buyer-Intent Interpretation

All 143 qualified observations in August 2026 fell into the Brand Recommendation cluster, the same pattern as July 2026 where all 161 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 either month. 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 Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• The qualified set (143 observations in August) differs from the raw collection (674 prompts); all percentages reference the qualified set.
• Small counts apply to several brands: Helping Hands (1 valid recommendation), Centria Autism (3), Trumpet Behavioral Health (3), and Acorn Health (4) 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; five met the qualification bar in August (ChatGPT, Copilot, Gemini, AI Mode, AI Overviews).

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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