Bitget Gives AI Trading Accounts Pushing Toward Agent-Native Markets

Bitget has introduced dedicated trading accounts for its AI agent GetClaw, enabling autonomous trade execution within live markets. The update allows the agent to operate independently using natural language inputs. Announced today, the move expands AI functionality from analysis into direct participation, a structural switch in how trading systems operate.

Bitget Enables AI Agents to Trade Independently

As per today’s disclosure, Bitget now allows GetClaw to execute trades through its own account environment. Within this structure, the AI agent can monitor markets continuously and manage positions in real time. It performs these actions without requiring manual intervention from users.

This development follows Bitget’s earlier launch of GetClaw as a zero-installation AI trading agent. Initially, the system focused on assisting users through insights and recommendations. However, the new account model extends its role into active execution under live conditions.

Source: Bitget

As a result, Bitget moves beyond traditional AI support functions. The platform now enables AI systems to act directly on predefined strategies. This shift introduces a new level of automation within trading environments.

Account Structure Separates User and AI Activity

Bitget designed the new structure using dedicated sub-accounts for AI agents. This setup separates user-controlled assets from agent-driven activity. As a result, users maintain visibility and control over how strategies operate within the system.

Users can define trading strategies in simple terms. Meanwhile, GetClaw executes, monitors, and adjusts positions based on those parameters. This approach allows continuous market interaction while maintaining clear operational boundaries.

This new development follows an earlier CoinGape report that Bitget expanded Agent Hub with AI tools for smarter trade execution.  Gracy Chen, CEO of Bitget, addressed the broader direction of this development saying,

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.

Integrated System Supports Agent-Native Trading

The introduction of agent accounts connects with Bitget’s wider system architecture. Through Agent Hub, AI agents access real-time data, analytical tools, and execution functions within one environment. Therefore, the platform removes the need for fragmented workflows.

This integration indicates a progression in AI deployment within trading systems. Earlier models focused on access and analysis. Now, Bitget combines intelligence with execution inside the same infrastructure.

Additionally, the system supports both human users and AI agents within a unified framework. This setup aligns with Bitget’s Universal Exchange model, where multiple asset classes operate under one account.

As AI-driven participation increases, trading systems adapt to support automated activity. Bitget’s structure enables agents to function alongside users in real time. As a result, analysis and execution now operate together within the same environment.