What AI washing is
AI washing is marketing that claims more artificial intelligence than the product actually contains. Sometimes it is a rules engine dressed up as machine learning. Other times a person is quietly running the "fully automated" workflow in the background. This matters to a mid-market buyer because the exposure has moved. Regulators used to chase companies that misled consumers. Increasingly they are chasing the ones that misled business buyers like you.
The enforcement timeline
In the United States the cases escalated quickly. In March 2024 the SEC settled its first AI-washing cases against two investment advisers, a modest US$400,000 in total[1]. By January 2025 it had charged its first public company. By April 2025 it had turned criminal. The founder of the "AI shopping app" Nate was charged with fraud after the app’s supposedly automated purchases turned out to be handled almost entirely by contract workers[2]. Through Operation AI Comply, the FTC took down the "world’s first robot lawyer" and, in a separate case, an AI content detector advertised as 98% accurate that independent testing put closer to 53%[3].
In every one of these cases, regulators punished the gap between the demo and the delivery. As the buyer, you absorb that cost directly, and any regulator turns up later, if at all.
The Australian picture
The same pattern is emerging in Australia. In October 2025 the ACCC took Microsoft to the Federal Court over how it presented Copilot-integrated Microsoft 365 plans to roughly 2.7 million Australian subscribers, alleging that it concealed cheaper Copilot-free options[5]. Penalties under the Australian Consumer Law have also increased. From 28 March 2026, the maximum rose to $100 million per contravention. Then-ASIC chair Joe Longo had already warned in 2024 that ASIC was "on the lookout" for AI washing, and its REP 798 review documented how far governance was lagging behind adoption.
One caveat. Neither ASIC’s nor the ACCC’s formal 2026 priorities name AI washing as a standalone item. The exposure comes from general misleading-conduct law rather than a dedicated AI offence. A board should not wait for a specific rule, because the existing law already applies.
Agent washing is the 2026 version
Gartner calls the current wave of overselling "agent washing": a chatbot, a script or some robotic process automation relabelled as an autonomous "agent". It estimated that of the thousands of vendors claiming agentic capability, only around 130 genuinely have it, and predicted that more than 40% of agentic AI projects will be cancelled by the end of 2027[4]. Given those numbers, a vendor promising an agent that runs your service desk end to end deserves scepticism by default.
A buyer’s test, taken from the case files
Each enforcement action above doubles as a question you can ask before signing. The FTC’s own guidance to sellers, turned around, works as a buyer’s checklist[6].
- Who or what actually does the work? Ask for the share of tasks completed with no human in the loop, and get it in writing (Nate’s was near zero; Presto’s over 70% needed a person)
- Who owns the model? A vendor reselling someone else’s AI as its own is a documented pattern, so ask what they built themselves
- Where is the independent accuracy evidence? "98% accurate" that tested at 53% is why you ask for third-party validation before trusting the number
- Run a proof of concept on your own data, with a measurable success metric agreed before you start
- Re-test after deployment. Models drift, so a claim that held on 1 January may not still hold on 1 June