Criminal organizations have rapidly adopted artificial intelligence tools, driving a 40 percent year-over-year increase in AI integration across crypto crime typologies in 2026. TRM Labs' AI-in-Crime Adoption Index, a composite measure of AI depth in major crypto crime, reached 54 out of 100 this year.
AI adoption by criminals streamlines operations by lowering the skill required for sophisticated schemes. A single operator can now target more victims and automate tasks that previously demanded large teams. The technology also enhances deception through synthetic media and large language models, making fraudulent activities more convincing.
Scams represent the most advanced category of AI adoption, reaching a "Mature" level in the TRM index and leading all crime types. Scammers leverage AI across operational stages, from generating victim leads and crafting lures to managing conversations that sustain the fraud.
Hacks and ransomware attacks also show increasing AI integration, both categorized at an "Emerging" level. Crypto hackers use AI to discover overlooked vulnerabilities in systems and to infiltrate IT firms, according to the TRM Labs report.
In contrast, narcotics and darknet markets remain at the earliest "Horizon" stage of AI adoption, indicating slower integration of these tools into their operations.
Blockchain transactions create a transparent record of criminal activity. While the underlying actors, tactics, and incentives for crime remain consistent with or without cryptocurrency, the public ledger records what most of the criminal economy attempts to hide. This on-chain data provides a measurable proxy for how AI is reshaping crime more broadly.
TRM Labs constructed the AI-in-Crime Adoption Index by scoring each crime type based on three distinct components measuring the depth of AI integration across operations. Every crime type evaluated by TRM Labs now exhibits a measurable AI footprint.
