What happened?
AI agents are being used more frequently to manage crypto trading, and a wave of new tools is emerging to automate strategies, alerts and execution. A CoinGecko report found 87% of traders would let AI manage at least 10% of their portfolio and 36% would let it manage the majority. Examples in the market today include ChatGPT Agent, AIQuant.fun, Passey Bot, DeepBot Pro and Lit Protocol’s Vincent, covering everything from simple alerts to scoped on‑chain automations.
Who does this affect?
Retail investors are the most visible group affected, since many are willing to hand over part of their holdings to AI for trading help. Developers, wallet providers and DeFi projects are also impacted because they’ll build, integrate and host these agents and need to manage permissions and security. Exchanges, liquidity providers and regulators will feel the downstream effects as automated agents change order flow, liquidity patterns and oversight needs.
Why does this matter?
Widespread adoption of AI trading agents can boost market efficiency and liquidity by automating routine decisions and expanding access to advanced strategies. But it can also raise correlated trading behavior, sudden volatility and systemic risk if many agents act on similar signals without robust risk controls. That’s why guardrails, transparency, scoped permissions and stronger risk management will be crucial for healthy market development and regulatory confidence.