HR AI Index

Index › Vendors › NICE WFM · September 2026 Edition

1 category · Named, not ranked

NICE WFM

1Judge labels

0First choices

1Negative labels

1 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

1 label, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. NICE WFM was named 1 time in Workforce planning, where ChartHop led with 31%. 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-market73 of 89

under the label threshold

Enterprisenot named

No model named it for this buyer.

In workforce planning · 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 NICE WFM 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
Workforce planning	Workforce planning and analytics	0%	73 of 89	100%	1	under 10 labels · led by ChartHop at 31%

Movement

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

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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative1 labelNone

First choiceAlternativeMentionNegative1 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.

No positive label carried a quote.

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.

“Traditional Legacy Scheduling Tools (e.g., certain iterations of NICE WFM) ... outdated desktop-style user interfaces” Qwen 3.7 Flash · Workforce planning · negative prompt · soft negative

Named alongside

The products named in the same answers as NICE WFM, over the 1 answer that named it. Took the first choice instead counts the answers where the other product was the first choice and NICE WFM was named but was not.

ProductSame answerTook the first choice insteadHead to head

Deel1 of 10Not in the top three

Oracle Fusion Cloud HCM1 of 10Not in the top three

Planetally1 of 10Not in the top three

Rippling1 of 10Not in the top three

SAP SuccessFactors1 of 10Not 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 NICE WFM. 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 1 of the 1 answers that named NICE WFM and are not a share of its labels.

Domains cited

aihr.com1

careerminds.com1

cubesoftware.com1

g2.com1

gartner.com1

gloroots.com1

interface-design.co.uk1

learn.g2.com1

omr.com1

selectsoftwarereviews.com1

Ten of the ten domain citations in answers naming NICE WFM came from somebody else's page.

Pages cited

aihr.com/blog/ai-workforce-planning1

careerminds.com/blog/workforce-planning-tools1

cubesoftware.com/blog/workforce-planning-software1

g2.com/categories/workforce-planning1

g2.com/products/nice-workforce-management/reviews1

gartner.com/reviews/market/workforce-management-applications1

gloroots.com/blog/playroll-reviews1

interface-design.co.uk/blog/hr-software-ux-benchmarking-20261

Pages are listed as the models cited 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 NICE WFM'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 NICE WFM, 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 nice.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.