Uber puts all 30,000 employees on ChatGPT Work

30,000 employees gain a new AI assistant for daily tasks and business operations.

Uber has expanded its partnership with OpenAI, rolling out ChatGPT Work to all 30,000 of its global employees. This follows a pilot program involving 1,000 employees earlier this year, which included teams from finance, operations, and product, with 80% of early adopters being non-engineers. Employees have used the AI agent for tasks such as analyzing operational data, localizing training materials, and building personalized dashboards. While Uber is fully adopting ChatGPT Work, the company is allowing teams to experiment with its applications, with a focus on identifying opportunities to automate job functions. Uber will track employee usage and workflow development to guide future AI deployments across the business. OpenAI has been rapidly scaling its enterprise offerings to compete with rivals like Anthropic, leveraging its established brand recognition in the business sector.

This widespread adoption signals a significant trend of large enterprises embedding generative AI tools directly into their core workflows, moving beyond experimental phases. Uber's strategy of broad deployment with flexible experimentation suggests a belief that generative AI's value will be unlocked through diverse, user-driven applications rather than top-down mandates. The company's emphasis on tracking usage indicates a data-driven approach to AI integration, aiming to quantify ROI and inform future strategic decisions regarding artificial intelligence across its operations.

The expansion also highlights OpenAI's success in capturing the enterprise market, intensifying competition with other AI providers like Anthropic. For employees, this means readily available AI assistance for a wide array of tasks, potentially boosting productivity and altering job responsibilities, particularly for non-technical roles. The move underscores the growing imperative for businesses to leverage AI for operational efficiency and innovation, with significant implications for workforce training and adaptation to AI-augmented work environments.