While we haven’t yet figured out how to prevent greenwashing in the corporate space, a new threat arises in the form of AI washing. What is it and how do we deal with AI washers? Let’s explore.
Artificial intelligence is the top priority for modern investors. All companies that boost their operations with AI have higher chances to attract the attention of both customers and sponsors. They also easily outdo competitors who are slower to adapt to innovative technology. Yet, where there’s hype, there’s often also unscrupulous efforts to benefit from it in an unfair way. That leads us to the new concept of AI washing.
AI Washing 101
AI washing are false or exaggerated claims that a product or service uses artificial intelligence (AI) when it actually doesn’t, or that it uses AI in much more significant and relevant ways than it does in reality.
For example, a company A states that it leverages cutting edge AI tools for its back-end processes, when in fact, most operations there are done manually or using simple automation. Or else, a startup B claims to provide AI-driven personal styling and shopping assistance, when the services are actually delivered by human employees in disguise.
The tendency to overestimate one’s AI capabilities has drawn the attention of both venture capitalists and regulators. Thus, the U.S. Federal Trade Commission (FTC) warned companies against making misleading AI claims, suggesting that penalties might apply. The number of securities class action filings connected to AI more than doubled in 2024, from seven in 2023 to 15 last year.
Meanwhile, investors are increasingly pressuring businesses to demonstrate returns on their generative AI investments. Almost all (90%) of organisations surveyed by KPMG in the first quarter of 2025 feel this pressure and acknowledge its importance, compared to just 68% in Q4 2024.
Why Companies Resort to AI Washing
Some argue that investor pressure is one of the reasons for businesses to hastily implement superficial AI features and make exaggerated AI claims.
Other reasons may include:
- claiming AI capabilities helps startups pitch the project to investors faster and easier, while they believe they might incorporate AI in their operations as soon as they have the funding;
- a desire to boost sales and partnerships by creating a more innovative public image prompts businesses to amplify their tech stack;
- using the hype to increase consumer confidence and engagement;
- absence of universal definition of what counts as “AI-powered” or relevant regulation to control such claims creates loopholes for unscrupulous marketing;
- FOMO – fear of missing out on something that everyone seems to be doing today and lose competitive edge, as a result.
Whatever the reason, AI washing seems to become more widespread each day. Jonathan Cohen, CIO of Robocap Asset Management, has recently noted that nearly a third of companies he encounters claim to have AI capabilities without true AI integration. “They might have an algorithm, but they don’t have machine learning, and they don’t have neural networks,” he said. “There is a lot of hype, and ‘AI washing’ going on, which is a bigger problem than greenwashing in my view.”
Real Life Examples of AI Washing
The theory might be clear, but let’s see how exactly AI washing reveals itself in real-life corporate settings. Here are a few cases where companies were caught on making false or misleading claims about their AI use and implementation in consumer products.
Nate Used Philippine Workers for AI Shopping Experience
Founded in 2018, the shopping app Nate was promoted as an AI-driven platform that could automate online purchases with a single tap. Instead of going through checkout processes on multiple websites, users could simply tap the “Buy” option in the Nate app and the e-commerce platform would automate purchases from different marketplaces with agentic AI. Or so they said…
Between 2019 and 2022, the startup’s founder Albert Saniger raised over $40 million from investors by making false claims about proprietary AI technology and misrepresenting the app’s capabilities as “able to transact online without human intervention.” As it appeared later, the app used hundreds of human call centre workers in the Philippines to manually process transactions.
To maintain the illusion of AI functionality, the company’s management restricted access to internal HR data, instructed employees to keep their work confidential, and directed contractors to remove any public references to their work with Nate. However, the truth still came to light. The Securities and Exchange Commission (SEC) has filed a civil complaint seeking penalties and a ban on Saniger serving in an executive role in future. Today, the former Nate CEO faces charges of securities fraud and wire fraud, each carrying a maximum sentence of 20 years.
Joonko Exaggerated All Its Business Metrics Including AI Capabilities
Joonko, an AI-driven hiring startup, was charged last year with defrauding investors of over $21 million. The company, founded by an Israeli citizen Ilit Raz, claimed to use AI to help corporate clients hire candidates in accordance with their diversity, equality and inclusion goals. It also vividly described its vast client base (more than 100 business customers, some from Fortune 500 companies, and more than 100,000 active job seekers) and robust efficiency, with earnings over $1 million in revenue. All of this was quite an exaggeration, to put it mildly.
Joonko allegedly misled the investors about its use of AI that could automatically connect customers with diverse candidates. According to the SEC, its tech stack was not nearly that advanced. All other misleading claims were supported by false bank statements and forged contracts. The company filed for bankruptcy in 2023. Raz now faces both civil and criminal charges from the SEC and DOJ. Potential punishment measures include a maximum of 20 years in prison for each count of securities fraud and wire fraud, as well as permanent injunction, civil penalties, disgorgement with prejudgment interest, and a ban on serving as an officer or director of a public company.
Innodata Flagship AI Product Is Allegedly Rudimentary Rather Than Innovative
In 2024, another class action lawsuit was filed against Innodata, an American company that provides business process, technology and consulting services and describes itself as “a global data engineering specialist focused on generative AI.” The firm is not a startup. It has 35+ years of experience and a solid client base consisting of media, publishing and information services companies, enterprises in the segments of aerospace, defense, financial services, and even government entities.
Despite its undeniable utility, investors were alerted to the firm’s promotion of its “proprietary, state-of-the-art” Goldengate AI platform. According to the legal complaint, this platform was primarily operated by offshore workers using basic software tools. The plaintiffs’ lawyers claimed that the company didn’t actually have functional sophisticated AI technology or invest in it as much as was advertised, nor did it plan to use AI much in new contracts, despite optimistic statements. The case is still in the early stages of litigation, so the result is not yet clear. In the latest development of the ongoing legal investigation, plaintiffs opposed Innodata’s motion to dismiss the amended lawsuit.
Evolv Technologies Is Accused of Overstating the Efficacy of AI Security Tools
Evolv Technologies, a twelve-year-old company focused on AI-powered security screening systems, has allegedly deceived investors about the potency of its flagship AI-powered product, Evolv Express, that is supposed to provide AI-based concealed weapons screening. Today, the company is facing multiple investigations and legal challenges over accusations of deceptive marketing and financial misconduct.
Namely, the U.S. Federal Trade Commission (FTC) has taken action against Evolv for overstating the capabilities of its Evolv Express scanners. Used in schools and stadiums, the tool allegedly often failed to detect weapons but flagged harmless items like laptops and water bottles. Besides, the U.S. Securities and Exchange Commission (SEC) has initiated an investigation over Evolv’s self-report that its financial statements from Q2 2022 through Q2 2024 contained material misstatements of the firm’s revenues, estimated between $4 million and $6 million.
Following these findings, Evolv’s Chief Financial Officer resigned, while Evolv’s board of directors terminated chief executive Peter George. The company’s co-founder Michael Ellenbogen stepped in as interim CEO.
GitLab Is Scrutinised for AI Development Tools
GitLab, AI-powered DevSecOps software platform, is currently facing a securities class action lawsuit filed by investors. They allege that the company has made false and misleading rosy statements about its AI technology being able to generate code more efficiently and demand for its AI-powered features. At the same time, the firm allegedly concealed disadvantageous facts about these capabilities.
The over-optimistic statements created a false impression of the company’s growth prospects and financial health, creating a tangible gap between investor expectations and the company’s real-world results. It ultimately affected the firm’s financial performance and significantly lowered GitLab’s full-year 2025 guidance. This announcement led to a significant market reaction, with the firm’s stock declining over 20% upon the legal case announcement.
Delphia and Global Predictions Were Not As AI-Powered Investment Advisors As They Seemed
Two different firms have made similar claims and were both targeted by regulators for AI washing. These were one of the first cases where the SEC showed its intention to enforce truthful representations about AI capabilities in the financial industry.
From 2019 to 2023, Toronto-based investment advisor Delphia claimed to use AI and machine learning to analyse diverse customer data, such as spending habits and social media activity, to inform its investment decisions. According to the SEC, it was not nearly true. Without either admitting or denying the legal findings, Delphia agreed to a cease-and-desist order, was censured, and paid a civil penalty of $225,000.
Meanwhile, San Francisco-based Global Predictions registered as an internet investment adviser in August 2023, claimed to be the “first regulated AI financial advisor” and offered its clients “expert AI-driven forecasts.” Guess what? These statements were also misleading. Besides, the firm topped AI washing with false claims of tax-loss harvesting services and misrepresentation of its assets under management. Just like Delphia, Global Predictions refused to admit or deny the findings, agreeing to a cease-and-desist order instead. The firm was censured and paid a civil penalty of $175,000.
How to Detect AI Washing?
Investors today are facing a hard task. On one hand, they are pressured by FOMO to take part in promising AI projects, which rule the world of venture capital. Last year, for example, AI-linked stocks have outperformed both U.S. and global indexes. Why wouldn’t one want to participate in the hype? On the other hand, it seems that more and more firms are taking advantage of investor interest, adding the word AI just about everywhere, just to secure the funding and take their share of the VC pie.
The problem is that an average investor can hardly verify the viability of AI-powered tools on the market and corporate claims. However, there are still some useful strategies that might reveal AI washing and prevent investors’ disappointment.
- Before investing in AI startup, check its track record of legal suits, you might find AI washing allegations;
- request information on compliance with relevant regulations such as the 2024 AI Act in Europe that demands clear accountability from companies using AI in critical sectors;
- check transparency of AI-labeled products, if the key data elements are missing, there’s likely a reason for that you won’t like;
- avoid too generic product descriptions that fail to explain what exactly AI does and how this is achieved, there’s a clear difference between trade secrets and ‘smoke and mirrors’ obscurity;
- check for real proofs of the AI tool efficacy, statistical improvements, real use cases, etc., verify their legitimacy if you can;
- seek information on what steps are taken to avoid bias in AI data and algorithms and which other precautions the firms take, if they’re not, their use of AI may be superficial or non-existent at all.
Bottom Line
AI washing occurs when companies exaggerate or fake their use of artificial intelligence to look more competitive and attract funding or attention. As AI becomes a hot topic for investors, some businesses are taking advantage of the buzz in an unscrupulous way. They might be claiming to use cutting-edge AI when they’re really relying on basic tools or even human workers behind the scenes.
Regulators like the SEC and FTC are starting to crack down on such claims, with more lawsuits and investigations emerging. Companies like Nate, Joonko, Innodata, Evolv, GitLab, and others have been accused of misleading investors about what their AI can actually do.
Why do they do it? Investor pressure, marketing hype, lack of clear rules, and fear of missing out all play a part. For investors, the reasons behind AI washing are not really that important, compared to the slim chances of profiting on someone’s AI bubble.
Although spotting AI washing can be tricky, red flags still exist. They include vague product descriptions, lack of real-world evidence, or no mention of how the firms handle AI risks like bias. In short, AI washing is becoming a serious issue, just like greenwashing or even more, so it pays to look past the buzzwords and dig deeper before buying in.
