IT AI Index

Index › Vendors › ChatGPT · September 2026 Edition

2 categories · Named, not ranked

ChatGPT

17Judge labels

0First choices

13Negative labels

9 of 12Models named it

2Categories

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

6 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. ChatGPT was named 6 times in AI coding and 1 other category, where GitHub Copilot led with 67%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business45 of 45

under the label threshold

Mid-market33 of 46

under the label threshold

Enterprise47 of 47

under the label threshold

In ai coding · 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 ChatGPT 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.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
AI coding assistants	Developer platform	0%	33 of 46	50%	4	under 10 labels · led by GitHub Copilot at 67%
ML platforms	Data platform	0%	76 of 99	50%	2	under 10 labels · led by Azure Machine Learning at 17%

Movement

This is the first edition on this tier, so no move can be computed for ChatGPT 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 ChatGPT across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Negative	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	1	0	1
Gemini 3.5 Flash	0	1	1
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	1	1
Mistral Small	0	0	0
DeepSeek V4 Flash	0	0	0
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	0	0	0
GLM 4.7 FlashX	1	1	2
MiniMax M2.5	1	0	1

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

Direct1 labelNone

Paraphrase1 labelNone

Comparative2 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative13 labelsNone

First choiceAlternativeMentionNegative17 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.

“Best for reasoning through hard code problems: Claude Code or ChatGPT/Codex” GPT-5.4 mini · AI coding · comparative prompt · alternative

“Best for explanations & multi\u2011language tasks: ChatGPT (GPT\u20114/Claude)” GLM 4.7 FlashX · AI coding · comparative prompt · alternative

“ChatGPT and Grok (relatively better but still concerns)” MiniMax M2.5 · ML platforms · negative 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.

“Avoid for Proprietary Work: Non-Enterprise Consumer Chatbots ... Standard, Free-Tier Web Chatbots (ChatGPT, Gemini, Claude)” Gemini 3.5 Flash · AI coding · negative prompt · hard negative

“Samsung banning ChatGPT after confidential code leaks” GLM 4.7 FlashX · AI coding · negative prompt · soft negative

“Seen in ChatGPT (2023 leak of chats/payment info)” Grok 4.1 Fast · ML platforms · negative prompt · soft negative

Named alongside

The products named in the same answers as ChatGPT, over the 17 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and ChatGPT was named but was not.

ProductSame answerTook the first choice insteadHead to head

Cursor13 of 171Not in the top three

GitHub Copilot12 of 175Not in the top three

Tabnine8 of 172Not in the top three

Amazon Q Developer8 of 171Not in the top three

Claude8 of 170Not in the top three

Claude Code8 of 170Not in the top three

Windsurf8 of 170Not in the top three

Google Gemini5 of 170Not in the top three

Aider2 of 170Not in the top three

Amazon SageMaker2 of 170Not 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 ChatGPT. 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 12 of the 17 answers that named ChatGPT and are not a share of its labels.

Domains cited

witness.ai6

arxiv.org5

augmentcode.com4

dev.to3

forbes.com3

ibm.com3

intuitionlabs.ai3

kusari.dev3

labs.cloudsecurityalliance.org3

privacyon.com3

Thirty-six of the thirty-six domain citations in answers naming ChatGPT came from somebody else's page.

Pages cited

witness.ai/blog/ai-coding-assistants-security5

arxiv.org/html/2509.20388v14

forbes.com/councils/forbestechcouncil/2025/03/21/ai-coding-assistants-17-risks-and-how-to-3

kusari.dev/blog/ai-coding-assistants-in-2026-4x-faster-10x-riskier-the-hidden-security-cos3

labs.cloudsecurityalliance.org/research/csa-research-note-ai-coding-assistant-attack-surfa3

privacyon.com/blog/ai-coding-assistant-security-risks-20263

wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2026-0056.pdf3

blog.incogni.com/ai-llm-privacy-ranking-20252

Pages are listed as the models cited them.

Names read as ChatGPT

What the judge wrote, as written, with how often. The vendor table decides that these count as ChatGPT; a claim can dispute any of them.

ChatGPT (GPT\u20114/Claude) 1ChatGPT / Codex 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 ChatGPT'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 ChatGPT, 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 chatgpt.com 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.