FBI Flags AI-Driven Scams Costing $893 Million

The FBI’s Internet Crime Complaint Center (IC3) reported that 22,364 internet crime complaints in 2025 referenced artificial intelligence, representing $893 million in reported losses. IC3’s annual publication, released April 6, 2026, marked the first time the agency broke out AI-related complaints as a separate category in its 25-year reporting history.

Attackers are weaponizing generative AI and synthetic media to scale and personalize fraud. The report calls out AI-driven creation of social media profiles, personalized conversations and synthetic audio/video. Those capabilities enable existing vectors—business email compromise (BEC), confidence/romance scams, employment and investment fraud—to become more convincing and automated, increasing both reach and plausibility of scams.

IC3’s 2025 dataset shows AI-related complaints contributed $893 million of the $20.9 billion total reported losses across 1,008,597 complaints (up from 859,532 complaints and $16.6 billion in losses the prior year). The FBI emphasizes that “People have manipulated video and audio similarly for decades, but the widespread availability of this developing technology makes it possible to create high-quality content,” and warns that “AI-enabled synthetic content is becoming increasingly difficult to detect and easier to make, which allows criminal actors to potentially conduct successful fraud schemes against individuals, businesses and financial institutions.” The coverage also notes PYMNTS Intelligence findings that content produced by AI can deceive both humans and automated systems, and that financial institutions are increasing investments in AI, behavioral analytics and cloud infrastructure to counter more sophisticated fraud.

This is not a novelty statistic—it's a signal that generative models and synthetic media are materially changing threat surfaces. Data scientists, ML engineers and fraud teams must reassess detection baselines, adversarial test suites and telemetry collection to spot higher-quality synthetic artifacts and scaled social engineering. Behavioral analytics, anomaly detection on communication patterns, provenance tracing and multi-factor authentication gains renewed priority.

Look for vendor and open-source tool updates that improve deepfake detection, provenance metadata standards, wider adoption of behavioral baselines, and regulatory or compliance guidance targeting synthetic content in financial workflows.