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What Workado advertised
The FTC complaint describes marketing for Workado’s AI Content Detector, also called AI Content Checker. Examples cited by the agency represented that the tool could predict whether text was human- or AI-generated with about 98% accuracy; some materials used 98.3%. The FTC’s April 2025 announcement rounded the figure to 98%.
- Advertising said the service could detect text associated with ChatGPT, GPT-4, Claude, Bard and other AI systems.
- Marketing described training on blog posts, Wikipedia, essays and other broad sources.
- Workado also promoted a “pro” function that could turn AI-written material into “undetectable” content.
The complaint identifies Workado as an Arizona company and notes a historical $49-per-month subscription from September 2023 through August 2024. That price is not current pricing and is not evidence of a present offer. The product scope also included an AI image detector introduced sometime in 2024.
Read the FTC administrative complaint.
What the FTC alleged was unsupported
The FTC alleged a violation of Section 5(a) of the FTC Act, which prohibits deceptive acts or practices. Its theory was not simply that an AI detector made occasional mistakes. The agency said Workado generalized a narrow, externally developed benchmark into a sweeping commercial claim without testing whether the result applied to the material and AI systems named in its advertising.
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Model provenance and training data
According to the complaint, Workado did not build, train or fine-tune the detector model. The model was publicly available through Hugging Face and identified as a RoBERTa academic detector. Its cited training material included human-written and ChatGPT-generated research abstracts, rather than the ordinary nonacademic material—such as blogs or Wikipedia—that Workado’s marketing suggested.
Missing validation for the advertised use
The complaint says Workado did not independently establish that the model achieved its advertised accuracy on the marketing and plain-language text customers were likely to submit. It also says the model was trained around ChatGPT rather than the full set of systems named in the company’s claims.
How the cited testing performed
| Testing result | What it means |
|---|---|
| 74.5% best result | The best result the complaint cites for a mixed set of human-created and AI-generated nonacademic content. |
| 53.2% correct identification | The cited rate at which the model identified AI-generated text in nonacademic material. |
| 98% to 98.3% advertised claim | The performance representation Workado used in marketing, according to the FTC complaint and press release. |
The 53.2% figure is the FTC’s description of a particular model test under a particular nonacademic evaluation condition. It is not a universal measurement of every version of every Workado product. The FTC press release characterized that result as roughly no better than chance for that task; that description should not be turned into a timeless claim that all AI detectors perform that way.
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Aggregate “accuracy” can also conceal the errors that matter most. False positives may cause human writing to be labeled AI-generated, while false negatives may allow AI text through. Results can change with the balance of human and AI examples, the text genre, the models that generated the samples, and whether text was edited, paraphrased or translated.
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What the consent order requires
The operative decision and order covers products that detect or purport to detect AI-generated or AI-altered text and images. It is broader than the text-detector claim that prompted the case.
Substantiated marketing claims
Workado must not make express or implied effectiveness claims about a covered product unless the claims are nonmisleading and supported by competent and reliable evidence when made and thereafter. Where appropriate, the order calls for competent and reliable scientific evidence.
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Preserving the evidence
The order requires Workado to retain the material needed to evaluate future claims, including test protocols, data and class distributions, preprocessing steps, analysis of training-and-testing overlap, the rationale for using the test data, and statistical analyses such as confusion matrices. That requirement makes the evidentiary record—not just the advertising copy—a compliance issue.
Customer notice and monitoring
- Workado must identify eligible customers who subscribed to its AI-detection products during the eligibility period, defined in the order as one year after issuance.
- Those customers must receive an FTC-approved notice within 180 days after the order’s issuance; customers identified later must be notified within 30 days.
- Workado must submit a compliance report one year after issuance and annual reports for the next three years.
Read the FTC decision and order.
What Workado did—and did not—admit
This was an FTC administrative enforcement and consent-order proceeding, not a criminal prosecution or a private damages lawsuit. In the order, Workado neither admits nor denies the complaint’s allegations, apart from specified jurisdictional facts. The legally accurate description is that the FTC alleged the claims were false, misleading or unsubstantiated and Workado resolved the matter through a consent order.
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The reviewed order materials describe injunction-like marketing restrictions, notice, recordkeeping and reporting obligations. They do not identify a monetary payment imposed in this matter. The FTC’s April 2025 release warned that violating a final order could trigger civil penalties of up to $53,088 per violation under the figure stated in that release; that is a potential consequence of a future violation, not a fine assessed here.
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See the FTC’s April 2025 announcement.
Why AI-detector claims are difficult to substantiate
Detector performance is tied to the exact task being measured. A credible claim should address:
- Representative data: The samples should match the genres, languages and users covered by the advertisement.
- Model coverage: Testing should include each named generator, not only one academic benchmark or one version of ChatGPT.
- Freshness: Results should reflect current generator versions and current text-modification techniques.
- Metrics: Accuracy should be accompanied by precision, recall, false-positive and false-negative rates, thresholds and uncertainty.
- Separate validation: Test data should not overlap with training data.
- Documented processing: Sampling, class balance, preprocessing and the reason the test set represents real use should be recorded.
- Ongoing monitoring: Models and evasion methods change, so a one-time score can age quickly.
The complaint describes signals such as repetitive wording, generic tone, sentence structure and probable word choices. Those features can also appear in human writing, which is why a detector score is a probabilistic signal rather than proof of authorship.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who can be affected by an erroneous score
The FTC complaint points to students wrongly accused of cheating, journalists whose work is rejected, and marketing or other commercial content treated as AI-generated. A score can also influence search ranking, grading, employment or reputation decisions. Schools, publishers, employers and platforms should therefore avoid automatic disciplinary or reputational action based only on a detector output; corroborating evidence and a chance to respond are essential.
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What the case means for AI-product marketing
The case does not establish that every AI detector is ineffective, and it does not ban AI-detection software. It shows the regulatory risk of presenting a narrow benchmark as universal performance—especially when the benchmark concerns different text, models or conditions from those in the advertisement.
For vendors, the practical lesson is to build a substantiation file before making a percentage claim: define the task, assemble representative and separate validation data, test every named model, publish the relevant error rates and limitations, and retest as the technology changes. For buyers, ask for those details rather than treating a single accuracy number as a guarantee.
CyberScoop reported the later settlement on August 29, 2025, describing the matter as part of a continuing contest between text generators, detectors and evasion tools. Read CyberScoop’s report.
Frequently Asked Questions
Did the FTC fine Workado?
The decision and order reviewed here do not impose a monetary payment. They require substantiated claims, evidence preservation, customer notices and compliance reports. The FTC separately warned that violating the final order could lead to civil penalties of up to $53,088 per violation under the amount stated in its April 2025 release.
Does the case prove that all AI detectors are useless?
No. The proceeding concerns the substantiation of Workado’s advertising and the gap between its broad claims and the testing described by the FTC. It does not establish that every detector fails or prohibit the technology.
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