Index › Products › IBM watsonx.ai · October 2026 Edition

IBM · 2 categories · Named, not ranked

IBM watsonx.ai

12Judge labels

0First choices

1Negative labels

8 / 14Models named it

2Categories

October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.

Standing

3 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. IBM watsonx.ai was named 3 times in ML platforms and 1 other category, where Azure Machine Learning led with 21%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market82 of 107

under the label threshold

Enterprise11 of 65

under the label threshold

In ml platforms · 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 IBM watsonx.ai 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	Since September 2026
ML platforms	Data platform	0%	82 of 107	50%	2	under 10 labels · led by Azure Machine Learning at 21%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
Enterprise AI assistants	Data platform	0%	65 of 145	0%	1	under 10 labels · led by ChatGPT at 25%

Movement

Since September 2026, IBM watsonx.ai held within the floor in all two categories: no change cleared 11 points.

Best category · ML platforms · by segment

Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

0%from 0% in September 2026

Inside the floor by 11 pointsRank 39 → 76 of 97

Enterprise=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.

0%from 0% in September 2026

Inside the floor by 11 pointsRank 14 → 11 of 55

All categories · Mid-market

Category	September 2026	Now	Change	Reading	Rank
ML platforms	0%	0%	=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.	Within noise	Rank 39 → 82 of 107
Enterprise AI	0%	0%	newNew since September 2026: not ranked then, 0% now.	New this edition	Rank 65 of 145, unchanged

Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.

The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions

By model

How each model treated IBM watsonx.ai across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.

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Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	0	0
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	0	0	0	0
Grok 4.20	0	0	0	0
Mistral Small	1	0	0	1
DeepSeek V4 Flash	0	0	0	0
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	0	0	0	0
Kimi K2	0	0	0	0
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	1	1	2
GPT-6 Luna	0	0	0	0
Muse Glimmer 30B	0	0	0	0

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

Direct4 labelsNone

Paraphrase0 labelsNone

Comparative6 labelsNone

Budget-constrained1 labelNone

Scale-constrained0 labelsNone

Negative1 labelNone

First choiceAlternativeMentionNegative12 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.

“consider Reclaim.ai or IBM Watsonx.ai for their lower entry prices and strong feature sets” Mistral Small · Enterprise AI · 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.

“High costs (especially IBM watsonx.ai and Google Cloud AI Platform)” MiniMax M2.5 · ML platforms · negative prompt · soft negative

Named alongside

The products named in the same answers as IBM watsonx.ai, over the 12 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and IBM watsonx.ai was named but was not.

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ProductSame answerTook the first choice insteadHead to head

Google Vertex AI10 of 122Not among the top eight

Databricks Mosaic AI9 of 125Not among the top eight

Amazon SageMaker9 of 123Not among the top eight

Azure Machine Learning8 of 121Not among the top eight

DataRobot6 of 121Not among the top eight

Dataiku6 of 120Not among the top eight

SAS Viya5 of 120Not among the top eight

H2O.ai4 of 120Not among the top eight

Snowflake Cortex AI4 of 120Not among the top eight

Domino Data Lab2 of 120Not among the top eight

A head-to-head page exists where both products are among a category's top eight. 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 IBM watsonx.ai. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 12 of the 12 answers that named IBM watsonx.ai and are not a share of its labels.

Domains cited

g2.com9

learn.g2.com7

checkthat.ai4

techdogs.com4

azumo.com3

dataiku.com3

eweek.com3

it-ai-index.com3

moveworks.com3

pickmysoft.com3

Forty-two of the forty-two domain citations in answers naming IBM watsonx.ai came from somebody else's page.

Pages cited

g2.com/categories/data-science-and-machine-learning-platforms7

learn.g2.com/best-machine-learning-tools7

g2.com/categories/machine-learning4

techdogs.com/top-10-technology-rankings/top-10-machine-learning-companies4

checkthat.ai/answers/what-are-the-best-machine-learning-platforms3

dataiku.com/blog/enterprise-machine-learning-platforms-how-to-choose3

eweek.com/artificial-intelligence/machine-learning-solutions3

learn.g2.com/best-data-science-ml-platforms3

Pages are listed as the models cited them.

Search and answers

Where IBM watsonx.ai stands in Google search beside where it stands in the models' answers.

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In search

Google, US estimates

Searches for its name, Google: 320 a month (“ibm watsonx.ai”)
AI search demand for its name, est.: 0 a month
Its own site: It sits on IBM's site (ibm.com), so there are no site figures for it alone

In answers

This edition

Share of first choices

rank 82 of 107 in ML platforms

Segment leader

21%

Azure Machine Learning

First choices: 0 across its categories
Named in: 12 answers
Its own site cited: in 12 of the answers that named it

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Names read as IBM watsonx.ai

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

IBM Watsonx.ai 1

Follow IBM watsonx.ai

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

The company

IBM is the company behind IBM watsonx.ai.

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On record

Company records

Also from IBM: IBM AI Fairness 360, IBM API Connect, IBM Apptio Cloudability, IBM Aspera, IBM Aspera Managed File Transfer, IBM Business Automation Workflow, IBM Cloud Databases, IBM Cloud Kubernetes and 98 more

In its own words

Stated by the vendor, not checked

Positioning: A next generation enterprise studio for AI builders to train, validate, tune and deploy AI models
ibm.com/products/watsonx-ai
For: AI builders
ibm.com/products/watsonx-ai
Price stated: Explore the pricing tiers for our trial, essentials and standard plans on IBM® watsonx.ai®. ibm.com/products/watsonx-ai
Free plan or trial: Start free trial ibm.com/products/watsonx-ai
Integrations claimed: 50 ibm.com/products/watsonx-data-intelligence
Customers named: UFCAddAIMyLÚA HealthBlendow GroupUHCW NHSCrushbankLockheed MartinELPEDISON
Not stated on the pages read: Starting price, certifications, hosting

What IBM watsonx.ai's own pages state, read October 5, 2026: ibm.com/products/watsonx-ai, ibm.com/products/watsonx-data, ibm.com/products/watsonx-data-intelligence, ibm.com/products/watsonx-ai/demo, ibm.com/products/watsonx-ai/llama. A claimed page can correct any of them.

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 IBM watsonx.ai'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 IBM watsonx.ai, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for IBM watsonx.ai by email, built from the raw record of the edition. It shows:

where IBM watsonx.ai is named, by buyer and by framing, and which cells hold its first choices;
the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
its vocabulary against the segment leader's, and the pages the models cited;
who was chosen in the answers that did not name IBM watsonx.ai, and every reason the record gives;
a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
one page of published figures cleared to show a buyer.