Uber Deploys ChatGPT Work to 30,000 Employees

Introduction

Uber has announced a company-wide deployment of ChatGPT Work, an agentic AI platform built on ChatGPT Enterprise, making it accessible to more than 30,000 employees globally. This rollout represents one of the largest-scale adoptions of an AI agent tailored for knowledge work, signaling a significant evolution in how enterprises integrate generative AI into daily operations.

The initiative expands from an initial pilot involving 1,000 employees and marks Uber’s first enterprise-wide implementation of an agentic AI system designed to execute multi-step tasks and deliver completed outputs. With integrations across core productivity tools, the platform aims to streamline research, data analysis, presentation creation, and cross-application workflows.

Agentic AI Meets Enterprise Productivity

ChatGPT Work is positioned as an autonomous agent capable of handling complex, multi-stage assignments within ChatGPT Enterprise. Unlike traditional chatbots, the agent can connect directly with widely used enterprise applications such as Google Drive, Gmail, Google Calendar, and Slack. This connectivity allows users to delegate tasks like summarizing documents, scheduling meetings, generating reports, and analyzing datasets without switching between platforms.

For large organizations like Uber, which operate across diverse functions—from operations and finance to marketing and product development—the ability to automate routine yet time-intensive tasks could significantly enhance productivity. The agentic model also supports voice and image generation, providing teams with multimodal capabilities to adapt to varying use cases.

Model Selection and Performance Optimization

As part of the deployment, Uber will leverage OpenAI’s latest frontier models, including GPT-6.1 Sol, which has been set as the default engine within ChatGPT Work. This model is designed to balance high performance with cost efficiency, a critical consideration for large-scale deployments where computational overhead can escalate rapidly.

Additionally, Uber’s developers and engineering teams will continue utilizing Codex, another OpenAI tool, to accelerate software development and refine coding workflows. This dual approach—combining general-purpose agents with specialized development tools—reflects a maturing strategy in enterprise AI implementation, where customization and scalability are prioritized.

Governance, Training, and Internal Support

To ensure responsible and effective adoption, Uber is backing the rollout with an internal AI skills library, pre-approved integrations, and dedicated employee training programs. These measures are intended to mitigate risks related to data privacy, compliance, and misuse of AI-generated content—all of which are growing concerns for security and engineering teams.

By establishing clear guidelines and educational resources, Uber aims to empower employees to use AI tools effectively while maintaining alignment with organizational standards. The company also plans to collaborate closely with OpenAI to gather insights on usage patterns, best practices, and measurable outcomes as the deployment scales.

Conclusion

Uber’s deployment of ChatGPT Work to over 30,000 employees illustrates the growing momentum behind agentic AI in enterprise environments. By integrating with familiar tools and leveraging advanced models, the company is positioning itself at the forefront of AI-driven transformation. As adoption grows, so too will the need for robust governance, secure integrations, and continuous monitoring—all areas where Grivyonx Technologies supports organizations through AI automation, DevSecOps, and cloud security services.