Key takeaways
- SEC increases scrutiny of corporate AI disclosures
- Misleading AI claims can violate securities laws
- Investors should examine revenue, spending and business risks
Imagine investing in a company that promises its artificial intelligence can outperform the stock market. Its presentations describe advanced algorithms, proprietary technology and impressive potential returns. But what if the company never developed the AI system it advertised?
That is the kind of misrepresentation attracting renewed attention from US regulators.
On October 30, SEC Enforcement Director David Woodcock told Reuters that the agency is examining AI companies' disclosures as concerns grow over inflated valuations, circular investments and enormous infrastructure commitments.
What Is AI Washing, and When Does It Become Illegal?
AI washing occurs when a business exaggerates or misrepresents its artificial intelligence capabilities, adoption or financial benefits.
Using AI-related language is not inherently misleading. The problem arises when companies make materially false statements or omit information investors need to evaluate those claims.
The SEC has already pursued such cases.
In March 2024, regulators charged investment advisers Delphia and Global Predictions with making misleading statements about their use of AI. The firms agreed to pay a combined $400,000 in civil penalties without admitting or denying the findings.
Delphia claimed to use customer data and machine learning to make investment decisions, despite lacking the advertised capabilities. Global Predictions similarly exaggerated its AI-powered forecasting services.
Another case involved Rimar Capital, whose representatives raised nearly $4 million from investors while misrepresenting an AI trading platform. The SEC announced $310,000 in combined civil penalties in October 2024.
These examples illustrate that securities laws apply to AI claims just as they do to claims about revenue, products or investment performance.
Why Are Circular AI Deals Worrying Regulators?
The latest concerns go beyond companies pretending to use artificial intelligence.
Consider a hypothetical chipmaker investing $10 billion in an AI startup. The startup then commits to spending much of that money buying computing infrastructure from the chipmaker.
Both transactions may be legitimate. However, investors should understand how much reported demand comes from independent customers versus financially connected companies.
Circular financing is not automatically fraudulent. The disclosure question is whether material relationships, dependencies and risks are accurately presented.
That distinction matters as technology companies commit unprecedented sums to AI infrastructure.
Amazon recently reported a $42.4 billion trailing annual free cash flow deficit despite accelerating cloud revenue growth.
Meanwhile, billions in data-center financing depend on expectations that customers will continue purchasing computing capacity.
These developments do not establish wrongdoing. They demonstrate why investors need clear information about revenue sources, financial commitments and business risks.
How Can Investors Identify Misleading AI Claims?
A useful starting point is distinguishing what a company promises from what it can demonstrate.
If management advertises AI-driven growth, investors should examine whether financial reports identify actual revenue, paying customers or measurable cost savings.
Coinpaper's guide to AI investment returns explains why revenue growth, margins and cash flow reveal more than infrastructure spending alone.
Financial disclosures also deserve attention. Companies may generate impressive accounting profits while facing significant cash requirements.
Those risks become more serious when expensive AI projects rely on borrowed money.
