When the Securities and Exchange Commission charged two investment advisers in March 2024 with making false claims about their use of artificial intelligence, then-Chair Gary Gensler did something unusual: he gave the misconduct a marketing-world label. He called it “AI washing,” borrowing the language that public-relations and communications professionals had already been using to describe a growing pattern of companies slapping “AI-powered” on products built with ordinary, years-old automation.
More than two years later, the practice has not slowed down. If anything, it has spread. PR strategists, investor-relations consultants, and communications directors say they are fielding pressure from executives and founders who want every product description, pitch deck, and earnings-call script to feature the term “artificial intelligence,” regardless of whether the underlying technology justifies it. The result is a credibility crisis that federal regulators, industry watchdogs, and the communications professionals closest to corporate messaging are all trying to contain at once.
The enforcement record so far
The SEC’s 2024 actions set the template. The agency charged Delphia Inc. and Global Predictions Inc. with making “false and misleading statements” about AI integration in their investment processes. Delphia had claimed it used machine learning and natural language processing to analyze client data and predict market behavior; Global Predictions marketed an “AI-driven” financial forecasting engine. In both cases, the SEC alleged the technology did not function as described. The firms settled, paying a combined $400,000 in civil penalties without admitting or denying the findings.
Months later, the SEC charged Rimar Capital and its owner, Itai Liptz, with a more brazen version of the same conduct: telling investors that AI drove the firm’s trading strategies when, according to the complaint, it did not. That case underscored that AI washing was not limited to careless marketing copy. Regulators treated it as securities fraud.
On the consumer side, the Federal Trade Commission launched Operation AI Comply in September 2024, bundling five enforcement actions targeting companies that made deceptive AI claims. The highest-profile target was DoNotPay, a startup that had marketed itself as “the world’s first robot lawyer” capable of replacing human attorneys. The FTC’s complaint alleged the company could not substantiate those claims and had never tested whether its output constituted competent legal advice. DoNotPay agreed to a consent order barring it from making similar representations without evidence.
Together, these cases moved the conversation from theoretical risk to documented enforcement. Misrepresenting AI capabilities can now trigger securities fraud charges from the SEC and deceptive-practices complaints from the FTC. The agencies have made clear that existing consumer-protection and securities laws apply to AI marketing, no new legislation required.
Why PR and communications professionals are pushing back
The regulatory actions validated concerns that people inside corporate communications teams had been raising internally for months. The pattern they describe is consistent across industries: a company that has used rule-based automation, basic statistical models, or simple decision trees for years suddenly begins describing those same tools as “AI-powered” or “machine-learning-driven” after watching competitors attract funding or media attention with similar language.
The pressure often flows top-down. Founders and C-suite executives see AI-labeled companies commanding higher valuations and want their own messaging to match. Communications teams are then asked to draft press releases, investor updates, and product pages that frame existing capabilities in AI terms. The professionals tasked with writing that copy are the ones most exposed to reputational and legal risk if the claims do not hold up.
Industry groups have started responding. The Public Relations Society of America (PRSA) updated its ethics guidance in 2024 to address AI-related communications, emphasizing that practitioners have an obligation to ensure accuracy in technology claims. The Chartered Institute of Public Relations (CIPR) in the UK published similar guidance. These are voluntary frameworks, not regulations, but they signal that the profession’s own institutions recognize AI washing as a systemic problem, not a fringe concern.
What makes the issue particularly difficult for communications professionals is the ambiguity of the term “AI” itself. There is no universally accepted technical threshold that separates “real” AI from enhanced automation. A rules-based chatbot and a large language model both get called AI in casual usage. That gray zone gives companies room to stretch definitions, and it puts the burden on PR teams to draw lines that even computer scientists debate.
The investor-money pipeline
The financial incentive driving AI washing is not subtle. According to CB Insights data, global funding for AI startups surged past $70 billion in 2024, with deal counts climbing even as overall venture capital contracted. Companies that position themselves within the AI category gain access to a pool of capital that has remained robust while other sectors tightened. For a startup or mid-stage company, adding “AI” to a pitch deck can be the difference between a meeting and a rejection.
That dynamic creates a self-reinforcing cycle. Investors allocate to AI-labeled companies, which raises valuations, which encourages more companies to adopt AI branding, which inflates the category further. The SEC’s enforcement actions suggest regulators view this cycle as a potential source of systemic misallocation: money flowing to firms based on capabilities they do not actually possess.
The problem extends beyond startups. Large enterprises have also been accused of overstating AI integration. Amazon faced pointed questions in 2024 after reports indicated that its “Just Walk Out” checkout-free grocery technology relied heavily on human reviewers in India rather than the autonomous computer-vision system the branding implied. Amazon has said the technology does use computer vision and sensor fusion, but the episode became a widely cited example of the gap between AI marketing and operational reality.
What regulators have not yet addressed
The enforcement actions to date target the clearest violations: companies that claimed fully autonomous AI systems where none existed, or that told investors AI was central to their strategy when it played no meaningful role. That leaves a wide middle ground untouched.
Neither the SEC nor the FTC has published detailed technical guidance specifying what qualifies a product as “AI-powered” versus “automation-assisted.” Without that clarity, companies operating in the gray zone, those using modest machine-learning components within largely traditional software, face genuine uncertainty about how to describe their products. The agencies have signaled that they will evaluate claims on a case-by-case basis using existing standards around materiality and substantiation, but that approach leaves room for inconsistent outcomes.
Leadership transitions add another layer of uncertainty. Gensler departed the SEC in January 2025. His successor, Paul Atkins, confirmed by the Senate in April 2025, has signaled a different regulatory philosophy, generally favoring lighter-touch oversight of emerging technologies. Whether the SEC will continue pursuing AI-washing cases with the same intensity under new leadership is an open question as of mid-2026. The FTC, meanwhile, has continued to reference AI deception in public statements, but no major new enforcement action on the scale of Operation AI Comply has been announced in 2026.
There is also no aggregated data on total investor losses attributable to AI washing. The individual SEC settlements involved relatively modest penalties. The broader economic harm, if any, from inflated valuations built on exaggerated AI claims has not been quantified in any public study. That gap makes it difficult to assess whether AI washing is a contained nuisance or a systemic risk to capital markets.
Where the pressure goes from here
For communications professionals, the practical takeaway is that the regulatory floor has been established. Companies can no longer treat AI as a consequence-free buzzword in investor materials or consumer marketing. The SEC has demonstrated willingness to bring fraud charges over AI misrepresentations, and the FTC has shown it will pursue deceptive AI claims in consumer products. Those precedents exist regardless of how aggressively either agency chooses to act in the near term.
The harder question is whether enforcement alone can change a culture of overstatement that is deeply embedded in how technology companies raise money and attract attention. PR professionals are positioned at the exact pressure point: they are the ones drafting the language, advising executives on what claims are defensible, and bearing professional risk when those claims collapse. Their alarm is not abstract. It is rooted in the daily reality of being asked to write things they are not confident are true.
The companies that navigate this environment successfully will likely be the ones that can document their AI capabilities with specificity: what models they use, what data trains them, what measurable outcomes they produce, and where human oversight remains essential. That level of transparency is harder to market than a vague “AI-powered” tagline, but it is also harder to prosecute. For an industry built on persuasion, the emerging standard is straightforward: if you cannot prove it, do not say it.
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*This article was researched with the help of AI, with human editors creating the final content.
