Uber deploys OpenAI agents to all 30,000 employees

The rollout of ChatGPT Work

Uber has officially begun deploying a new AI tool called ChatGPT Work to its entire workforce of 30,000 employees. This initiative is part of a broader effort to integrate advanced artificial intelligence into the daily operations of the global transportation company. As reported by pymnts.com, the tool is specifically designed to handle tasks that are significantly more complicated than a standard chat request.

Unlike basic AI interfaces that simply answer questions, this new agent is built to execute multi-step workflows. It can spend several hours on a single project if the complexity of the request requires it. This allows employees to move beyond simple prompts toward a model where the AI can produce finished materials like documents, slides, and web apps.

Uber's leadership views this as a way to empower the workforce to solve problems more efficiently. The company wants to provide every team member with the tools necessary to innovate and shape the future of the business. By giving everyone access, Uber hopes to foster a culture of rapid problem-solving and technological adoption across all departments.

Capabilities and functionality

The primary strength of ChatGPT Work lies in its ability to take action across a user's existing files and various applications. This means the agent can connect different software tools that employees use every day to complete a single objective. For example, it can research specific information and then automatically prepare a meeting brief based on those findings.

Employees can use the agent for a wide variety of professional responsibilities. These include creating full presentations, analyzing complex data sets, and managing workflows that span multiple platforms. The goal is to deliver finished work rather than just providing a starting point for a human to complete later. This shift toward 'agentic' behavior is a key differentiator for this specific OpenAI release.

While most of the company will use ChatGPT Work for general business tasks, specialized teams will maintain their current workflows. The developers and software engineering teams at Uber will continue to use OpenAI's Codex. Codex is a specific model designed for software development and coding workflows, ensuring that technical teams have the right tools for their specific needs.

Strategic AI partnerships

This deployment is the latest in a series of deep integrations between Uber and OpenAI. Previously, OpenAI powered a driver-facing assistant that translated live marketplace data into positioning advice for drivers. This helped drivers understand where to go to find more rides based on real-time information.

The company also utilized OpenAI technology for a rider-facing feature that includes a voice interface. This allows passengers to book rides using natural speech rather than manually typing into an app. These existing features demonstrate how Uber has already been weaving AI into the core user experience for both drivers and riders.

The new rollout of ChatGPT Work expands these capabilities internally. While the previous tools focused on the marketplace and customer experience, this new deployment focuses on the internal productivity of the company. It represents a move to optimize the 'back office' and corporate functions with the same technology used for the consumer-facing products.

The growth of enterprise AI

The move by Uber highlights a significant trend in the growth of OpenAI's enterprise business. Reports indicate that this sector is driving substantial gains in annualized revenue for the AI company. The revenue for this segment is expected to reach at least $70 billion by the end of the year, a notable increase from the $50 billion reported at the end of September.

OpenAI President and Co-Founder Greg Brockman noted that teams can now tap into a portfolio of frontier models to connect their daily tools. This reflects a broader market shift where companies are looking for ways to get more done by connecting disparate software systems. By integrating these agents, organizations aim to reduce the manual friction of moving data between different apps.

For Uber, the goal is to see what their various teams can build with these new capabilities. The company is positioning itself to be an early adopter of agentic workflows at scale. As more companies follow suit, the ability to deploy agents that can work independently over several hours will likely become a standard requirement for large corporate infrastructures.