Bitget Surpasses 1M Users and $1.2B in AI Agent Trading Volume

Bitget has crossed a symbolic line in AI-driven trading. The exchange says its new Bitget AI ecosystem now serves more than one million users and has generated $1.2 billion in AI agent trading volume. The announcement puts automation closer to the center of crypto trading, not just as a support tool, but as part of execution itself.

Bitget turns AI into trading infrastructure

Bitget is no longer presenting AI as a simple chatbot attached to an exchange. The move fits its wider push toward AI and diversified trading, already visible in a recent Bitget report showing that 51% of crypto investors are turning to AI tools.

The company is building a unified environment where market analysis, trading execution, and risk management sit inside the same ecosystem. This matters because traders often move between too many tools. Charts are in one place. Signals are elsewhere. Execution happens on another screen.

Bitget AI tries to reduce that fragmentation. The platform already includes more than 58 AI-powered tools. This is not a small experiment hidden in a corner of the product. Bitget is making AI part of its trading architecture, and the numbers suggest users are testing that shift at scale.

The strongest part of the announcement is not only the one million users. It is the $1.2 billion in trading volume generated through AI agents. That figure shows that AI is moving beyond passive market commentary. At the center of the ecosystem are GetClaw and GetAgent. GetClaw gives real-time market insights without installation. GetAgent focuses on strategy execution and automated trading. Together, they create a bridge between reading the market and acting on it.

This is where Bitget’s message becomes more ambitious. The exchange wants AI to help traders organize strategies, deploy them, and interact with the market faster. In other words, the assistant is slowly becoming an operator. It does not just explain the market. It begins to act inside it.

An agent-native exchange takes shape

Bitget describes this direction as an “agent-native exchange.” The phrase may sound technical, but the idea is simple. Human traders and autonomous agents can operate side by side in the same market environment.

That model changes the role of the trading platform. An exchange is no longer only a venue for orders. It becomes a workspace where strategies can be created, tested, adjusted, and executed with AI support.

This also explains the importance of Agent Hub. The developer platform gives access to APIs and model integrations. It is designed for builders who want to create AI-driven strategies and connect them to Bitget’s trading infrastructure. The exchange is not only courting retail traders. It is also speaking to developers, strategy creators, and professional users.

The next step: AI Trading Playbooks

Bitget also plans to roll out AI Trading Playbooks in the coming months. The feature is currently in beta. It aims to let professional traders create and backtest strategies using natural language.

This could become useful for traders who understand market behavior but do not want to write complex code. A human-readable strategy can be easier to review, modify, and share. Still, execution remains the sensitive part.

The company says the system will include data SDKs, trading harness standards, and marketplace distribution. That points to a broader goal. Bitget wants AI strategies to become products that can be hosted, scaled, and potentially distributed inside its ecosystem.

Bitget’s AI push arrives at a moment when exchanges are trying to become more than crypto marketplaces. Its recent expansion into tokenized finance, including products linked to pre-IPO exposure, shows the same direction: more assets, more automation, and a wider trading environment, as seen in Bitget’s IPO Prime move toward AI-linked tokenized finance.