Cryptocurrency exchange Bitget has confirmed a major organizational shift by purchasing enterprise-wide access to Anthropic’s Claude for its entire workforce. The move allocates roughly $200 per employee per month — totaling approximately $433,400 monthly or $5.2 million annually — for all 2,167 staff, marking a decisive transition of artificial intelligence from optional experimentation to core workplace infrastructure.
The decision positions AI as a horizontal layer across the company rather than a tool confined to specific departments. Compliance officers, customer support teams, developers, marketing staff, and operations personnel will have standardized access to the large language model. Bitget’s approach mirrors a broader industry pattern in which crypto exchanges increasingly embed AI into internal workflows — from market surveillance and fraud detection to code generation and regulatory reporting — beyond the user-facing trading tools already deployed.
Bitget’s public-facing AI push has already shown scale: its AI-powered trading ecosystem surpassed one million users and generated $1.2 billion in volume across more than 58 tools as of May. The internal rollout extends that philosophy, aiming to reduce friction in daily operations and improve speed of execution. Potential gains include faster ticket triage in customer support, accelerated policy checks for compliance, and streamlined smart contract audits. However, the investment also introduces risks; employees relying on AI-generated drafts without rigorous human review could create compliance gaps or data-handling issues, prompting the need for robust internal training and oversight.
The competitive context is clear. Centralized exchanges operate at the intersection of high-frequency data, retail sentiment, and regulatory pressure. By standardizing AI access, Bitget aims to boost productivity without proportional headcount increases. Failing to manage the rollout effectively — through fragmented tool use or inadequate governance — could lead to security vulnerabilities and inconsistent quality. This enterprise commitment signals that AI is becoming a baseline operational layer for exchanges, and firms that integrate it successfully may gain lasting advantages in both efficiency and user trust.
