October 14, 2025
Artificial Intelligence (AI) is transforming the way companies work by streamlining healthcare, automating financial services, and reshaping industries at a pace unlike anything we’ve ever seen. With rapid growth comes risk: some businesses may be tempted to exploit the complexity and novelty of AI to mislead regulators, harm investors, overstate capabilities, or defraud government programs. Take for example Rimar Capital USA, Delphia (USA) Inc. and Global Predictions, all of whom have incurred substantial monetary penalties for false and misleading statements about their purported use of AI.
AI Is Fueling New Fraud Schemes
Fraud tied to AI can take many forms. Here are a few hypothetical examples:
Healthcare & Insurance
- Scheme: Inflate bills for “AI-powered” diagnostics, imaging tools, or predictive analytics that are either unproven, don’t function as described, or replicate existing manual processes.
- Example: A company markets an AI system that claims to detect early-stage cancers with 95% accuracy, but in practice it performs no better than standard methods. Insurers and patients are billed at a premium.
Government Contracts
- Scheme: Overstate capabilities of AI to win defense, intelligence, or administrative contracts. They may claim autonomous decision-making, real-time data analysis, or superior predictive accuracy that does not exist.
- Example: A defense contractor exaggerates that its AI surveillance tool can detect threats with near-perfect accuracy, leading to a multimillion-dollar contract award. Later, the system produces error-prone results.
Financial Services & Technology
- Scheme: Misrepresent the use of AI to investors, regulators, or customers to inflate valuations, justify price increases, or secure venture capital.
- Example: A fintech firm touts an “AI-driven risk model” for loans, but the model is a basic regression analysis with human overrides. Investors are misled about technological edge and growth potential.
Data Misuse & Compliance Fraud
- Scheme: Cut corners on compliance, bias testing, or data privacy, while telling regulators and customers its AI tools are ethical, fair, and privacy-reserving.
- Example: A social media company claims its recommendation algorithm is “bias-free” and compliant, but internal audits show it systematically favors certain content and collects unauthorized personal data.
Cross-Cutting Themes
While these sector-specific examples highlight different forms of AI-related fraud, they are not isolated. Common threads run across industries:
- AI as a Buzzword: Just as “blockchain” and “crypto” were misused in past fraud waves, “AI” is being deployed as a hype-driven label to lure capital, contracts, and credibility.
- Enforcement Lag: Regulators are still developing AI-specific frameworks, creating opportunities for misrepresentation before oversight catches up.
Have You Witnessed AI-Related Misconduct?
If you have non-public information about AI-related misconduct or know of false statements made to the marketplace or government about AI products or services, your information may form the basis of a whistleblower case. Federal and state whistleblower programs and laws, including the False Claims Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act, offer protections for those who come forward, and in certain circumstances, financial awards for exposing fraud.
Why act now? Because AI is moving faster than the law. Regulators and courts rely heavily on individuals who have the courage and knowledge to come forward and report wrongdoing. Whistleblowers have been essential in protecting taxpayers, patients, consumers and investors in every major wave of technological change. AI is no different and your knowledge could make all the difference.