AI Agents Transform Trading Dynamics
On April 6, 2026, Bitget, recognised as the world’s largest Universal Exchange, unveiled a new account structure. This innovation allows its AI trading agent, GetClaw, to independently execute trades within a dedicated account environment.
GetClaw is now capable of executing real trades autonomously, utilising natural language instructions. It continuously monitors markets and manages positions in real time without the need for manual intervention.
Gracy Chen, CEO at Bitget, stated, “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.”
This development builds on Bitget’s previous launch of the GetClaw AI agent, which required no installation and served as a persistent trading partner.
Advancing AI in Trading Bitget expanded
The Agent Hub by introducing advanced analytical AI skills and integrated data tools. These enhancements directly connect market analysis with execution, marking a progression from access to intelligence, and now to independent execution. Within Bitget’s Universal Exchange model, both crypto assets and tokenized traditional instruments operate within a unified account structure.
The addition of agent accounts extends the platform’s functionality beyond manual trading. The AI account structure reflects a shift in AI application within trading. Initially, AI systems focused on analysis and recommendations, but now they observe markets continuously and act on defined strategies.
By assigning dedicated accounts to AI agents, Bitget extends AI capabilities into direct participation under live market conditions. This allows strategies to be deployed with greater transparency and control. Users can define strategies in simple terms, while GetClaw autonomously executes, monitors, and adjusts positions within predefined parameters.
The separation of user-controlled assets from agent-driven activities ensures greater transparency and control. Bitget’s approach integrates AI directly into its trading environment, allowing both human users and automated systems to operate within the same infrastructure. Through Agent Hub, AI agents access real-time data, analytical tools, and execution capabilities without relying on fragmented workflows.
As AI-driven participation in trading grows, environments evolve to support both human and machine-driven activity. This evolution shapes what is increasingly known as agentic trading. As automation integrates across markets, trading systems evolve toward environments where analysis and execution operate together in real time.
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Last updated: 10 April 2026, 12:24 pm
