HR AI Index
Index Vendors › Adapt Learning · September 2026 Edition
Adapt · 1 category · Named, not ranked

Adapt Learning

15Judge labels
0First choices
2Negative labels
7 of 12Models named it
1Category
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, every buyer segment counted.
Standing
7 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Adapt Learning was named 7 times in Course authoring tools, where Articulate 360 led with 22%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In course authoring tools · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Adapt Learning for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Course authoring toolsLearning and development0%20 of 860%7under 10 labels · led by Articulate 360 at 22%

Movement

This is the first edition on this tier, so no move can be computed for Adapt Learning yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Adapt Learning across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini01102
Gemini 3.5 Flash01001
Perplexity Sonar00000
Grok 4.1 Fast01001
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K202002
GLM 4.7 FlashX00000
MiniMax M2.500101

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative3 labelsNone
Budget-constrained6 labelsNone
Scale-constrained2 labelsNone
Negative4 labelsNone
First choiceAlternativeMentionNegative15 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“A free, open-source framework that creates responsive, vertical-scrolling courses” Gemini 3.5 Flash · Course authoring tools · budget prompt · alternative
“Choose Adapt if budget is a primary concern and you have technical resources” Kimi K2 · Course authoring tools · comparative prompt · alternative
“Need free/open-source and have technical support: Adapt” GPT-5.4 mini · Course authoring tools · budget prompt · alternative
“Free (open-source) | Fully responsive HTML5 courses” Grok 4.1 Fast · Course authoring tools · budget prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

No model argued against it.

Named alongside

The products named in the same answers as Adapt Learning, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Adapt Learning was named but was not.
ProductSame answerTook the first choice insteadHead to head
iSpring Suite12 of 151Not in the top three
Adobe Captivate11 of 150Not in the top three
H5P10 of 154Not in the top three
Articulate Rise 3609 of 153Not in the top three
Articulate 3608 of 153Not in the top three
Elucidat8 of 150Not in the top three
Lectora7 of 150Not in the top three
Easygenerator5 of 151Not in the top three
dominKnow | ONE5 of 150Not in the top three
ActivePresenter3 of 151Not in the top three
A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Adapt Learning. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 10 of the 15 answers that named Adapt Learning and are not a share of its labels.

Domains cited

colossyan.com7
atomisystems.com5
confirm.com5
elearningindustry.com5
elearningsolutionslab.com5
gartner.com4
intellum.com4
lingio.com4
proprofstraining.com4
coursebox.ai3

Forty-six of the forty-six domain citations in answers naming Adapt Learning came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Adapt Learning

What the judge wrote, as written, with how often. The vendor table decides that these count as Adapt Learning; a claim can dispute any of them.
Adapt 1
Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Adapt Learning's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Adapt Learning, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at adapt.digital is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

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