How AI Search Is Recommending Learning Management Systems: Monthly Trends

Executive Summary

Docebo leads the category in October 2026 with a 44.0% valid recommendation coverage rate, ahead of TalentLMS at 43.1% by less than a point, and Moodle at 35.5%. That is a narrow top of the table. The gap between the leader and the second brand is 0.9 points, and the third brand sits 8.5 points behind the leader. No brand moved far enough against the July baseline to register as a significant riser this month, and the category's only significant baseline movement is a decline for Blackboard (Anthology).

The strongest current-month movement belongs to Docebo, which rose 5.9 points from September to October, a change the benchmark treats as significant against the prior month. Moodle matched that margin, up 5.9 points prior to current, and Absorb LMS rose 6.4 points prior to current, with 175 valid recommendations in October and a 15.5% top-three rate. Against the July baseline those three sit at 44.0%, 35.5%, and 33.1% respectively.

Blackboard (Anthology) is the clearest decliner. It is down 10.6 points against the July baseline, from 17.8% to 7.2%, and the benchmark classifies that as a significant decline. Its top-three rate fell 4.7 points over the same span, from 9.0% to 4.3%. The one countervailing figure is a modest prior-to-current improvement of 1.2 points, from 6.0% in September to 7.2% in October.

The three months between the July baseline and October did not run in a straight line. August compressed every brand in the category to single-digit coverage, September restored most of it, and October held that restored level while reshaping the top of the table. TalentLMS held the top spot on coverage in July and again in September; October is the first month in the series where Docebo leads, and its 31.4% top-three rate is the highest in the category this month.

Each monthly run begins with 800 prompt-surface observations (527 unique questions) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 620 were relevant and 180 were irrelevant. The public metrics use the 529 observations that survive both qualification stages. In July 2026, the run also began with 800 prompt-surface observations (468 unique questions), with 467 observations surviving qualification. September 2026 drew 800 prompt-surface observations across 508 unique questions and qualified 585 observations.

Key Findings

AI Response Inconsistency Alerts

One high-severity factual inconsistency was detected this month, spanning two AI platforms.

TalentLMS

AI platforms provided conflicting information about TalentLMS pricing at high severity. When asked how much the LMS fee is, Google AI Overviews stated that TalentLMS offers flat entry-level subscriptions starting around $149 per month for up to 40 users, while Copilot stated that TalentLMS costs $229 to $579 per month. The two claims cannot both hold, because the lower figure falls outside the range the other platform gave. Google AI Overviews drew on third-party pricing guides, including pages from Disprz, Educate-Me, and SoftwareFinder. Copilot drew on a different set, including CompanyLMS pages and an Educate-Me pricing guide. One source cited on the Copilot side, a CostBench learning-management pricing page, was flagged with high confidence as carrying the $229 to $579 monthly range.

Benchmark Context

Questions This Section Answers

• How many prompt-surface observations qualified for the October benchmark, and how does that compare to July?
• What changed in the recommendation-shaped answer share between July and October?

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 observation count moved from 467 in July to 447 in August, up to 585 in September, and settled at 529 in October. The AI surface universe held at six canonical families across the whole series.

Benchmark-Level Metrics

The recommendation-shaped answer share in October, at 40.5%, is the highest in the series. September sat at 30.1% and August at 6.3%, when the qualified set contracted sharply on both measures before recovering.

AI Recommendation Trend

Questions This Section Answers

• Which learning management systems lead the category in October 2026, and how close is the top of the table?
• Which brands lost the most coverage against the July baseline?

Docebo Holds the Lead as the Top of the Table Compresses

No brand exceeded normal month-to-month variation against the July baseline except Blackboard (Anthology), whose decline is significant. The rest of the category-level picture comes from the combination of several smaller movements: Docebo and Absorb LMS up modestly against July, most other brands down between half a point and five points.

What Changed This Month

Questions This Section Answers

• Why did Docebo widen its lead in October, and did that come from new mentions or better placement?
• What drove Blackboard (Anthology)'s significant decline, and where did its recommendations go?

Docebo: The Lead Widens on Strength, Not on a Rival's Slip

Docebo rose 3.1 points against the July baseline, from 40.9% to 44.0% valid recommendation coverage. The sharper figure is the prior-to-current move: up 5.9 points from September's 38.1%, which the benchmark treats as significant. In October the brand holds 233 valid recommendations across the qualified set of 529 observations.

That rise is not simply presence. Raw mention presence moved only 2.9 points over the series, from 75.6% in July to 78.5% in October, while the top-three rate rose 8.3 points, from 23.1% to 31.4%. Rank-one placements moved from 10.7% to 11.7%, with 62 rank-one answers in October against 50 in July.

The distinction to notice: Docebo was already being mentioned in roughly three quarters of qualified observations in July. What changed is how often those mentions convert into a top-three placement.

Highest-priority diagnostic: which prompts and which surfaces drove the top-three conversion gain, and whether the same answers displaced a specific brand.

Absorb LMS: The Largest Current-Month Riser

Absorb LMS rose 6.4 points from September to October, from 26.7% to 33.1%, a significant prior-to-current move. Against the July baseline of 31.3%, the brand is up 1.8 points, which is within normal variation.

The brand holds 175 valid recommendations in the October qualified set. Its top-three rate is essentially flat against July, at 15.5% against 15.6%, and its rank-one rate is unchanged at 1.5%, or 8 answers. Raw mention presence rose 2.2 points over the series, from 45.6% to 47.8%.

The distinction to notice: Absorb LMS moved sharply month over month without moving its placement profile against the baseline. That pattern points to a change in how many qualified observations included the brand rather than a change in where the brand placed when included.

Highest-priority diagnostic: whether the October gain came from additional prompts entering the qualified set or from prompts where Absorb LMS was previously absent.

Moodle: High Presence, Moderate Conversion

Moodle rose 5.9 points from September to October, from 29.6% to 35.5%, a significant prior-to-current move. Against the July baseline of 39.8%, the brand is down 4.3 points, within normal variation. It holds 188 valid recommendations in October.

The structural figure for Moodle is the gap between presence and placement. Raw mention presence is the highest in the category at 83.4% in October, down only 3.3 points from July's 86.7%. Its top-three rate sits at 15.7% and its rank-one rate at 4.7%, with 25 rank-one answers.

The distinction to notice: Moodle is mentioned more often than any other tracked brand, yet its top-three rate (15.7%) trails Docebo's (31.4%). Its October coverage places it third in the category despite leading on presence.

Highest-priority diagnostic: what AI systems say about Moodle in the observations where it appears but is not placed in the top three.

Blackboard (Anthology): The Category's Only Significant Baseline Decline

Blackboard (Anthology) sits at 7.2% coverage in October, down 10.6 points from the July baseline of 17.8%, the only decline in the category large enough to be treated as a meaningful shift. The brand moved up 1.2 points from September's 6.0%. It holds 38 valid recommendations in October.

The loss is concentrated in placement rather than presence. Raw mention presence is 51.8% in October against 51.2% in July, a 0.6 point rise. The top-three rate fell 4.7 points over the same span, from 9.0% to 4.3%. Net sentiment fell from 0.5 to 0.1, the lowest reading in the category. Rank-one placements are 0.2%, or a single answer.

The distinction to notice: Blackboard is mentioned in about half of qualified observations, a rate comparable to Absorb LMS, but converts those mentions into valid recommendations at 7.2% against Absorb's 33.1%. The benchmark shows the conversion gap widening against Docebo by 13.7 points across the series.

Highest-priority diagnostic: which brands take the recommendation in the high-presence, low-conversion Blackboard observations, and which sources those answers draw on.

TalentLMS: Rank-One Strength Behind a Flat Coverage Line

TalentLMS sits at 43.1% coverage in October, down 1.7 points from the July baseline of 44.8%, within normal variation, and 3.4 points up from September. It holds 228 valid recommendations, the second-highest count in the category.

The standout figure is rank one. TalentLMS places first in 14.4% of qualified observations, up 5.4 points from July's 9.0%, the highest rank-one rate in the category. That is 76 rank-one answers in October, against 42 in July. Its top-three rate rose 2.8 points over the same span, from 23.5% to 26.3%.

The distinction to notice: the brand sits second on coverage by less than a point while leading on first-position placements. Coverage and rank one are separate signals, and TalentLMS's advantage is concentrated in the second.

Highest-priority diagnostic: which prompts TalentLMS wins outright, and whether those are the same prompts where the pricing conflict described above appears.

Buyer-Intent Interpretation

Questions This Section Answers

• What buyer-intent clusters did the October benchmark measure, and which ones were empty?
• Why can't the benchmark explain how AI systems position brands on pricing or head-to-head comparisons?

In October, all 529 qualified observations fell into the Brand Recommendation cluster. The pricing and value and multi-brand comparison clusters were empty, as they were in July, August, and September. The benchmark therefore measures which brands AI systems recommend in direct response to buyer requests. It cannot yet answer how AI positions brands on price, value, or head-to-head comparison, and the pricing inconsistency noted above sits outside the qualified set for that reason.

Brand Opportunity Summary

Questions This Section Answers

• Which brand had the largest current-month gain, and what diagnostic question does that raise?
• Which prompts and surfaces should brands investigate to understand why each one moved?

The benchmark identifies where attention is warranted across all ten brands; a company-level analysis is needed to explain why each brand moved as it did.

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 Visibility Market Discovery research program.

• AI Visibility Industry Market Methodology
• AI Visibility Industry Market Metrics
• AI Visibility Industry Market Standards

Report-Specific Interpretation Notes

• October's qualified set of 529 observations sits between July's 467 and September's 585. Brand-level percentages are calculated within the qualified set, not the 800 total prompts collected.
• Small counts apply at the lower end of the category: D2L Brightspace holds 37 valid recommendations and Blackboard (Anthology) holds 38 in October, making these figures more sensitive to response-mix changes than leaders with more than 150 valid recommendations.
• Blackboard (Anthology) is the only brand whose baseline movement is large enough to be treated as a meaningful shift. The rest of the category-level change comes from several smaller movements in the same direction.
• Movement between months identifies changes worth investigating. It does not by itself establish what caused those changes.

Next Step

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

Beneath each aggregate percentage sits a set of unanswered questions: which high-intent prompts are won, which competitor takes the recommendation when a brand loses, what attributes AI associates with each option, and which external sources shape those answers. In a month where the top two brands sit within a point of each other and one brand's decline is the only significant baseline movement, understanding which prompts convert matters more than the headline figure.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers why a brand holds or loses recommendation credit and where the next improvement opportunity sits.

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