Forty cents of every venture capital dollar invested in crypto companies in 2025 went to firms building products that combine artificial intelligence and crypto, more than double the 18 cents a year earlier.
“AI is increasingly entering crypto not as a parallel narrative, but as part of crypto’s own product and infrastructure stack,” Binance Research said, citing data from Silicon Valley Bank, noting that this shows “how quickly AI is becoming embedded within crypto roadmaps.”
That pressure is visible in crypto’s shift from AI “co-pilots” to “agents.” Co-pilots help users analyze information, while agents can monitor conditions and execute actions. In trading environments, where timing affects outcomes, reducing the gap between insight and execution can change behavior.
The trend is part of a wider surge in AI spending. Crunchbase data shows AI companies raised about $242 billion in the first quarter of 2026, or roughly 80% of global venture funding. Gartner estimates total AI spending will reach $2.52 trillion this year.
Crypto leading the AI push
This trend, however, isn’t surprising.
As capital concentrates in one area, it often pulls adjacent sectors along with it, pushing firms to adapt their strategies and shorten product cycles, Binance Research wrote.
While almost all sectors are trying to incorporate AI into their business models, the report says that crypto platforms have moved faster than traditional finance in deploying such systems. This is due to support from always-on markets in the digital assets sector and programmable infrastructure, whereas TradFi faces market-hour constraints and intermediary systems that agents must pass through.
For example, the research noted that on Binance’s AI Pro beta, nearly half of the activity on a recent day, 45.7%, was triggered by the system rather than users.
These interactions came from scheduled tasks and monitoring systems, pointing to growing use of AI tools that run in the background without prompts.
Adoption of AI solutions is uneven across the 17 exchanges and brokers Binance Research surveyed. Risk management, market signals, and fraud detection are standard, while user-facing tools such as copy trading, chatbots, and portfolio advisors are present in only 47% to 71% of them.
Several major platforms have shipped agentic products this year, moving AI closer to monitoring and execution within set guardrails. That compresses the value chain between identifying an opportunity and acting on it, Binance Research added.
That means the competitive landscape will shift from who’s integrating AI features to who’s owning users’ decision-making loops, the report noted.