"Operation AI Comply" 2 Years Later: Continued Enforcement Against Misleading Claims

Nearly two years have passed since the Federal Trade Commission (FTC) launched "Operation AI Comply" in September 2024, announcing a coordinated set of enforcement actions targeting companies that rely on artificial intelligence (AI) to "supercharge deceptive or unfair conduct." Since the announcement, enforcement against misleading AI claims has not softened. If anything, scrutiny of this practice, sometimes referred to as "AI washing," has intensified, involving attention from both federal regulators and industry self-regulatory bodies.

The FTC: Sustained Focus

When the FTC announced Operation AI Comply in 2024, it may have been perceived as a one-time enforcement push. Nearly two years later, there is continued enforcement pressure following the themes laid out by the initial sweep. Last year, the FTC initiated more than a dozen cases associated with AI washing, targeting companies who allegedly exaggerated or fabricated AI capabilities when marketing their products and services.

FTC Chairman Andrew Ferguson framed these enforcement actions as pro-innovation, rather than as anti-technology. In April 2026 FTC testimony before the U.S. Senate Committee on Commerce, Science, and Transportation, he described the agency's commitment to "fostering American innovation" and "encouraging growth in the AI market by targeting bad actors who undermine innovation through deception." The underlying theory is clear: If consumers and businesses cannot trust AI-related marketing claims, the entire marketplace suffers.

Several enforcement patterns are worth noting:

Scrutiny into B2B Marketing Claims. Historically, the FTC's consumer protection authority has primarily been associated with claims made by companies to individual consumers. In the AI washing context, however, the FTC has also focused on business-to-business (B2B) marketing. Of the FTC's most recent AI washing cases, many involve claims made to other businesses rather than end consumers. This is a meaningful development for companies that market AI tools to enterprise clients: The same substantiation requirements and deception standards apply, regardless of whether the audience is a consumer or sophisticated business purchaser.

Revival of "Means and Instrumentalities" Doctrine. In several recent actions, the FTC charged not only the company making the AI claims directly to customers, but also vendors that supplied the deceptive marketing materials downstream. Under the "means and instrumentalities" doctrine, a company that provides another entity with the tools to deceive – marketing materials, sales pitches and responses to customer questions – can itself face liability.

The SEC: AI Washing as Securities Fraud

The U.S. Securities and Exchange Commission (SEC) has pursued AI washing through a different lens: investor protection and accurate disclosure. Beginning with enforcement actions in 2024 against investment advisors for misrepresentations of their use of AI, the SEC made it clear that such conduct violates existing anti-fraud provisions.

Under current SEC leadership, the Cyber and Emerging Technologies Unit has identified AI-related misrepresentations as a priority enforcement area. In 2025, the SEC signaled that it expects to pursue enforcement cases involving accurate and transparent representation of available and emerging technology.

Beyond SEC enforcement, companies should be alert to class action securities litigation risks. Plaintiffs have filed multiple cases this year against public companies and their officers and directors alleging securities fraud based on AI washing theories.

The BBB NAD: Self-Regulatory Scrutiny

The National Advertising Division (NAD) is a cross-industry self-regulatory program administered by Better Business Bureau (BBB) National Programs that reviews national advertising for truthfulness and accuracy. NAD decisions and recommendations do not have the force of law; they create a public record that regulators and plaintiffs' counsel can and do reference. NAD has not hesitated to challenge exaggerated or unsubstantiated AI marketing claims.

NAD highlighted several recurring issues in AI advertising:

• premature availability claims, where companies market AI features as available when the technology has not yet been released
• deceptive demonstrations, where promotional content implies a level of performance that the AI cannot consistently deliver
• lack of objective substantiation, where productivity or efficiency claims rest on user perceptions rather than measurable data

Each of these patterns represents a high-risk area for enforcement action.

Practical Steps to Mitigate AI Washing Risk

Companies that market AI-powered products or services may consider the following steps to mitigate AI washing exposure:

Review the Claims Being Made About the Product. Review materials for AI-related claims, including website copy, pitch decks, earnings call scripts and SEC filings. Identify statements that assert AI capabilities and verify the claims can be substantiated with documentation showing what the technology actually does.

Distinguish Aspiration from Current Capability. Marketing language that describes future plans or goals ("we are working on …"; "… in development") may carry different risk than present-tense claims ("our AI-powered platform can do X, Y and Z," "running on our proprietary AI"). Present-tense claims need to be backed up by present-tense substantiation.

Assess B2B Representations and Vendor Exposure. If a company provides AI products and marketing materials to downstream sellers or resellers, evaluate whether those materials make claims about AI capabilities that the product cannot meet.

Document Substantiation Contemporaneously. Maintain records of testing, validation and performance data that support AI-related marketing claims at the time they are made.

Monitor the Evolving Landscape. Companies should track enforcement actions, consent order language, investigative priorities and industry guidance to identify the specific practices or issues most likely to be targeted by regulators.

Conclusion

Across a spectrum from willful deception to simply perceived overstatements of a product's AI capabilities, AI washing exposes companies to enforcement risk from multiple directions.

The enforcement activity of the past two years reflects a shared recognition across agencies and self-regulatory bodies that the AI marketplace depends on trust, and trust requires accurate representations even in a highly competitive environment where business teams may be compelled to push the envelope on marketing their products' capabilities. Companies that take a more disciplined approach to substantiating and documenting their AI claims will be better positioned to avoid enforcement exposure and build credibility with customers, investors and regulators.

Holland & Knight's Data Strategy, Security & Privacy Team has experience advising on product counseling, including proactive advisory work, regulatory response and lawsuit defense. If you have any questions regarding best practices for your organization, please reach out to a member of our team.