IT AI Index

Index › Vendors › Workiva · September 2026 Edition

2 categories · Named, not ranked

Workiva

16Judge labels

0First choices

3Negative 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

7 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Workiva was named 7 times in GRC and 1 other category, where Vanta led with 14%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business64 of 71

under the label threshold

Mid-market23 of 77

under the label threshold

Enterprise17 of 47

under the label threshold

In grc · 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 Workiva 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
GRC platforms	Security operations	0%	23 of 77	0%	6	under 10 labels · led by Vanta at 14%
Compliance automation	Security operations	0%	46 of 54	0%	1	under 10 labels · led by Drata at 37%

Movement

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

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

Direct2 labelsNone

Paraphrase3 labelsNone

Comparative7 labelsNone

Budget-constrained1 labelNone

Scale-constrained0 labelsNone

Negative3 labelsNone

First choiceAlternativeMentionNegative16 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.

“Choose Workiva if reporting, controls, and board-ready reporting matter a lot.” GPT-5.4 mini · GRC · direct 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 Workiva, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Workiva was named but was not.

ProductSame answerTook the first choice insteadHead to head

Drata11 of 164Not in the top three

Vanta11 of 164Not in the top three

ServiceNow Integrated Risk Management11 of 161Not in the top three

AuditBoard10 of 161Not in the top three

MetricStream10 of 161Not in the top three

OneTrust9 of 160Not in the top three

Hyperproof8 of 160Not in the top three

Archer7 of 160Not in the top three

LogicGate Risk Cloud6 of 161Not in the top three

Diligent One6 of 160Not 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 Workiva. 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 13 of the 16 answers that named Workiva and are not a share of its labels.

Domains cited

expertinsights.com7

orbiqhq.com7

vanta.com6

optro.ai5

hackernoon.com4

riskonnect.com4

apono.io3

complyjet.com3

devopsschool.com3

enzuzo.com3

Forty-five of the forty-five domain citations in answers naming Workiva came from somebody else's page.

Pages cited

expertinsights.com/compliance/the-top-governance-risk-compliance-grc-platforms6

orbiqhq.com/compliance-automation/best-grc-software6

optro.ai/blog/best-grc-tools4

riskonnect.com/best-grc-software-platforms-20264

vanta.com/resources/best-grc-software-solutions-for-enterprises4

apono.io/blog/top-10-governance-risk-and-compliance-grc-software-solutions3

complyjet.com/blog/best-grc-software3

devopsschool.com/blog/top-10-grc-governance-risk-compliance-platforms-features-pros-cons-c3

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 Workiva'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 Workiva, 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 workiva.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.