How AI Search Is Recommending TV Streaming Services: Monthly Trends

Executive Summary

Hulu remains the category leader for AI-driven recommendation visibility, holding a 37.1% valid recommendation coverage rate in September 2026, down from 40.6% in July but up from August's 34.7%. The recovery from August's dip still leaves Hulu 3.5 points below its July baseline, and the movement is classified as stable. The gap to the second-place brand, YouTube TV at 33.5%, stands at 3.6 points, compared with a 10.8-point lead in July — the category has closed in around the leader through gradual gains among the chasing pack rather than any single decisive change.

Netflix was the strongest riser across the three-month window, climbing from 22.3% coverage in July to 25.2% in August and 26.5% in September, a cumulative gain of 4.2 points. Netflix's rank-one recommendation rate rose to 16.4% in September from 12.7% in July, making it the most frequently cited first-choice option in the category, and its average recommended rank improved to 1.36, the strongest in the dataset.

Peacock recorded the largest single-month decline in September, falling from 28.4% coverage in August to 25.0%, a drop of 3.4 points that reversed August's slight uptick; Peacock's July-to-September change is a decline of 3.2 points. Disney+ posted a two-month downward streak from 29.7% in July to 27.6% in September, and Paramount+ fell 2.7 points from August to September after rising in the prior month. None of these movements were large enough to be flagged as unusual for the category, which is classified as quiet this month: all ten tracked brands are stable.

Relative to the July baseline, the clearest change in category structure is the narrowing gap between Hulu and Netflix, which stood at 18.3 points in July, compressed to 9.5 points in August, and sits at 10.6 points in September. Netflix also moved from trailing Peacock by 5.9 points in July to leading Peacock by 1.5 points in September, a gap that moved in Netflix's favor every month of the series.

Each monthly run begins with 800 prompt-surface observations (573 unique questions in July; 603 in August; 587 in September) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor in all three months; 783 were relevant and 17 were irrelevant in July, versus 774 relevant and 26 irrelevant in August, and 767 relevant and 33 irrelevant in September. The public metrics use the 727 qualified observations in July, 697 in August, and 728 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.

These qualified counts are the denominator for every brand-level percentage in this report. September's 728 qualified observations sit close to July's 727, keeping the two periods on comparable footing.

Benchmark-Level Metrics

The following category-level metrics summarize the shift from the July baseline to the September benchmark.

August, the intermediate month, saw the qualified set dip to 697 observations. September's 728 qualified observations returned the set to near-July size, while the recommendation-shaped answer share for September (20.3%) remained slightly below July's 21.0%.

AI Recommendation Trend

The Leader Held While the Chasing Pack Converged Quietly

Hulu retained the top position in September, but its margin over YouTube TV narrowed to 3.6 points from 10.8 points in July. The category's spread among the actively tracked brands compressed through steady, individually modest gains rather than a single decisive move. YouTube TV, HBO Max, Disney+, and Amazon Prime Video all sit within 10 points of the leader.

The shift in the leaderboard reflects a combination of several smaller movements rather than one dominant move. No brand's month-to-month change this month was flagged as unusual, and the category as a whole is classified as stable.

What Changed This Month

Hulu: Leader Stable, Coverage Below Baseline

Hulu's coverage fell from 40.6% in July to 34.7% in August, then recovered to 37.1% in September, leaving the brand 3.5 points below its July baseline. The movement is classified as stable.

Hulu's raw mention presence remains the highest in the category at 98.2% in September, up from 97.2% in July, so the coverage change is not a presence problem. The shift shows up in placement: Hulu's rank-one rate fell from 4.4% in July to 2.2% in September, and its top-three rate dropped from 16.8% to 12.4%. Hulu appears in nearly every answer but is recommended at the top of the list less often than it was in July.

The distinction for Hulu is between presence and recommendation placement. The brand is nearly always mentioned, but its share of first-choice and top-three recommendations has eased even as overall coverage recovered from August.

Highest-priority diagnostic: Which prompt types shifted Hulu's rank-one and top-three placements downward, and which services are taking the first-choice slot when Hulu is mentioned but not recommended first?

YouTube TV: Steady Rise Across Two Months

YouTube TV climbed from 29.8% coverage in July to 30.7% in August and then 33.5% in September, a 3.7-point gain from baseline across two consecutive months of increase. The brand now sits second, 3.6 points behind Hulu, the closest any service has come to the leader across this series.

The coverage gain came with a rise in raw mention presence, from 76.5% in July to 82.7% in September. YouTube TV's rank-one rate of 7.7% and top-three rate of 9.9% both sit slightly below their July levels, meaning the coverage growth reflects broader mention rather than stronger top placement.

YouTube TV's rise is a presence-driven story. It is being mentioned in more AI answers, and it appears in more recommendation shortlists, but its share of top-three placements has not kept pace with its coverage growth.

Highest-priority diagnostic: Which surfaces or prompt contexts drove YouTube TV's presence gain, and is the coverage increase converting into top-three recommendations in specific query types?

Netflix: Strongest Riser and Rank-One Leader

Netflix rose from 22.3% coverage in July to 25.2% in August and 26.5% in September, a 4.2-point gain from baseline across two consecutive months of increase — the largest cumulative gain in the category. Its rank-one rate rose to 16.4% from 12.7% in July, and its top-three rate reached 17.7%.

Netflix now leads the category in rank-one recommendations with 119 first-choice placements in September, up from 92 in July. Its average recommended rank improved from 1.89 in July to 1.36 in September, the strongest in the category.

Netflix's coverage still trails several rivals, but its rank-one share means it is the most frequent first choice when AI systems recommend a streaming service in this dataset. Coverage and rank-one leadership are separate signals, and Netflix leads on the latter.

Highest-priority diagnostic: Which prompt types and AI surfaces generated Netflix's rank-one gains, and is the concentration in original content, value, or another use case?

Peacock: Largest Monthly Decliner

Peacock fell from 28.4% coverage in August to 25.0% in September, down 3.4 points month over month and 3.2 points from July's 28.2%. The 25.0% coverage figure corresponds to 182 valid recommendations out of 728 qualified observations.

Peacock's raw mention presence rose from 78.1% in July to 82.4% in September, so the coverage decline happened despite broader presence. Its top-three rate fell from 4.5% in July to 2.5% in September, while its rank-one rate eased from 1.5% to 1.1%.

Peacock is being mentioned more often but recommended in the top three less often. The gap between its presence gain and its placement decline is the signal worth investigating.

Highest-priority diagnostic: Which query types moved Peacock out of top-three recommendations, and which competitor is taking those placements?

Disney+: Two-Month Downward Streak

Disney+ declined from 29.7% coverage in July to 28.8% in August and 27.6% in September, a two-month downward streak totaling 2.1 points from baseline. The 27.6% figure corresponds to 201 valid recommendations out of 728 qualified observations.

Disney+'s rank-one rate fell from 4.7% in July to 2.2% in September, while its raw mention presence rose from 88.4% to 89.6%. Top-three placement also eased from 16.6% to 13.3%.

Disney+ maintains high presence but is converting less of it into top-of-list recommendations. The two-month streak suggests a pattern rather than a one-off adjustment.

Highest-priority diagnostic: Which surfaces shifted Disney+ out of rank-one placement, and is the decline concentrated in specific content or use-case prompts?

The Converging Middle of the Category

Three notable-gap pairs show the category restructuring across the series. The Hulu-to-Netflix gap narrowed from 18.3 points in July to 10.6 points in September, though it moved unevenly (compressing to 9.5 points in August before widening slightly in September). The Hulu-to-YouTube TV gap narrowed every month of the series, from 10.8 points in July to 4.0 in August to 3.6 in September. Netflix moved from trailing Peacock by 5.9 points in July to leading by 1.5 points in September, a gap that moved in Netflix's favor every month.

These are observations about the distribution of measured outcomes rather than verdicts on any single brand's strategy. The category's recommendation credit is being spread more evenly across services than it was in July.

Buyer-Intent Interpretation

Across all three months, the qualified observations fell into the discovery and consideration cluster (Brand Recommendation): 727 in July, 697 in August, and 728 in September. The Pricing & Value and Multi-Brand Comparison clusters recorded zero qualified observations in all three months. The public benchmark therefore measures which services AI recommends in general discovery queries, but it does not yet answer commercial questions about price sensitivity, value positioning, or head-to-head comparison outcomes.

This is a meaningful gap for streaming executives. Pricing and bundling are central to this category's competitive dynamics, yet the current benchmark captures no pricing-analysis or comparison-stage observations within the tracked buyer-intent clusters.

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: Individual recommendation counts for several brands are small relative to the qualified set. A change of a few valid recommendations can produce a multi-point movement, especially for brands with lower coverage. Treat small-count movements as directional, not definitive.
• Qualified denominator vs. raw collection: Brand-level percentages use the qualified observation set (727 in July, 728 in September), not the 800 raw prompts per month. The raw collection includes prompts that were irrelevant or reserved.
• Directional analysis: Month-over-month movement identifies changes worth investigating; it does not by itself establish cause. No brand's month-over-month movement in September was flagged as unusual, and the category is classified as quiet.
• Surface breadth: The benchmark covers six AI surface families: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. Keyword variants are rolled up into their canonical families.

Next Step

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

Beneath the aggregate percentages sit the questions that matter for strategy: which high-intent prompts does a brand win, which competitor takes the recommendation when a brand loses, what attributes do AI systems associate with each option, and which external sources shape those answers. The public benchmark shows that Netflix leads in rank-one visibility while Hulu leads in coverage, but it does not reveal which specific queries produce those outcomes or why.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It isolates the gaps, identifies the evidence sources associated with AI recommendations, and shows which prompts represent the highest-value opportunities for improvement.

Request an AI visibility audit