AI tools are transforming cryptocurrency-related illicit activities, with overall adoption climbing sharply according to recent findings from blockchain intelligence firm TRM Labs. The company’s 2026 AI-in-Crime Adoption Index scores the use of artificial intelligence across crypto crime at 54 out of 100, placing it in the “emerging” category.
According to insights from TRM Labs, this marks a rise from roughly 28 in 2024 and reflects approximately a 40 percent increase over the past year.
Scammers account for most of the growth and have reached a “mature” stage of AI integration, while hacking and ransomware operations remain in the emerging phase.
Activities linked to narcotics and darknet markets are still at the earliest “horizon” stage.
Ari Redbord, Global Head of Policy and Government Affairs at TRM Labs, explained the shift clearly: artificial intelligence has not created entirely new forms of crime. Instead, it has eliminated previous limitations.
The barrier of required technical skill has dropped dramatically, the potential scale of operations has expanded, and the creation of false identities has become industrialized.
Tasks that once demanded a coordinated team can now often be handled by a single individual with access to widely available AI subscriptions.
Evidence of this acceleration appears strongly in fraud.
The proportion of cryptocurrency scam reports that involve AI elements—such as deepfakes or automated chatbots—has increased by as much as thirteen times since 2022.
Losses attributed to deepfake-related scams in 2026 so far have already exceeded the entire total recorded for 2025 by 263 percent, underscoring how quickly these tools are being operationalized.Hackers are also incorporating AI more aggressively.
North Korean-linked cyber actors, for example, are employing deepfake techniques to infiltrate organizations through fake IT worker profiles, running AI-supported social engineering campaigns, and using artificial intelligence to help identify software vulnerabilities.
Digital asset hacks hit a record 201 incidents in the first half of 2026—more than double the figure from the comparable period the year before.
Roughly 61 percent of the associated losses, about $600 million, were tied to North Korea-linked activity.
A large share of total losses stemmed from a small minority of incidents that typically involved compromises of private keys or credentials rather than purely code-based exploits.
One notable development highlighted in the findings is JadePuffer, described as the first fully agentic ransomware attack.
In this case an AI system managed the entire process—from reconnaissance and credential theft through lateral movement and encryption—without continuous human direction.
TRM Labs also noted that ready-made, no-code ransomware packages are now available for relatively low prices, further lowering entry barriers.
Because a significant portion of illicit proceeds eventually moves across public blockchains, on-chain patterns serve as a useful indicator of broader trends in AI-enabled crime.
The overall picture shows that while the fundamental categories of crypto crime remain familiar, the speed, scale, and accessibility of these operations have changed markedly.
As artificial intelligence continues to mature, both criminal actors and those working to disrupt them will likely rely more heavily on advanced tools. The data from TRM Labs illustrates how quickly the landscape is evolving and why monitoring these shifts remains essential for investigators, compliance teams, and the wider digital asset ecosystem.