In 2025, approximately 40% of venture capital invested in crypto companies was allocated to firms that developed products integrating artificial intelligence and crypto, marking a significant increase from the 18% recorded in the previous year. According to Binance Research, citing data from Silicon Valley Bank, "AI is becoming an integral part of crypto's product and infrastructure stack, rather than a parallel narrative." This trend is reflected in the shift from AI "co-pilots" to "agents" within the crypto space. While co-pilots assist users in analyzing information, agents are capable of monitoring conditions and executing actions, thereby reducing the gap between insight and execution in time-sensitive trading environments.
The surge in AI spending is part of a broader trend, with Crunchbase reporting that AI companies raised approximately $242 billion in the first quarter of 2026, comprising roughly 80% of global venture funding. Gartner estimates that total AI expenditure will reach $2.52 trillion by the end of the year.
Crypto is at the forefront of the AI push, a trend that is not entirely unexpected. As capital concentrates in a particular area, it often pulls adjacent sectors along with it, prompting firms to adapt their strategies and accelerate product development cycles, as noted by Binance Research.
Although various sectors are attempting to incorporate AI into their business models, crypto platforms have been more agile than traditional finance in deploying such systems, thanks to the support of always-on markets and programmable infrastructure in the digital assets sector. For instance, Binance Research observed 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, with these interactions originating from scheduled tasks and monitoring systems, indicating the growing adoption of AI tools that operate in the background without prompts. The adoption of AI solutions is uneven across the 17 exchanges and brokers surveyed by Binance Research.
While risk management, market signals, and fraud detection are standard, user-facing tools such as copy trading, chatbots, and portfolio advisors are present in only 47% to 71% of them. Several major platforms have introduced agentic products this year, bringing AI closer to monitoring and execution within established guardrails, thereby compressing the value chain between identifying an opportunity and acting on it, according to Binance Research. As a result, the competitive landscape is expected to shift from who is integrating AI features to who is controlling users' decision-making loops, as noted in the report.