PRESS RELEASE.
The introduction of agent accounts reflects a shift in how AI is being applied within trading. The beginning saw systems focused on assisting users through analysis or recommendations but recent models are capable of observing markets continuously and acting on defined strategies. By assigning dedicated accounts to AI agents, Bitget extends this capability into direct participation under live market conditions.
“Sooner or later emerging financial markets are going to be filled with AI agents trading on behalf of users. We’re preparing the infrastructure to run this on scale,” said Gracy Chen, CEO at Bitget.
The use of dedicated sub-accounts provides clear separation between user-controlled assets and agent-driven activity, allowing strategies to be deployed with greater transparency and control. Users can define strategies in simple terms, while GetClaw executes, monitors, and adjusts positions within predefined parameters.
This approach reflects a broader architectural direction. Rather than treating AI as an external layer, Bitget is integrating AI directly into its trading environment, allowing both human users and automated systems to operate within the same infrastructure. Through Agent Hub, AI agents can access real-time data, analytical tools, and execution capabilities without relying on fragmented workflows.
As AI-driven participation grows, trading environments are evolving to support both human and machine-driven activity. This transition is shaping what is increasingly described as agentic trading, where systems move from supporting decisions to actively participating in markets.
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