Uber expands ChatGPT Work to 30,000 employees

From pilot to global rollout

Uber is significantly expanding its internal use of artificial intelligence by granting ChatGPT Work access to more than 30,000 employees. This large-scale rollout follows a smaller initial pilot program that involved only 1,000 people. The company is moving toward a model where AI is a standard part of the global workforce's toolkit.

The rollout focuses on an AI agent designed to handle complex, multi-step tasks rather than just providing simple answers. By providing this to a wide range of teams, Uber aims to integrate AI into various daily operations. This shift represents a growing trend in how large organizations manage the adoption of generative technology.

The expansion comes at a time of heightened corporate concern regarding AI security. While many companies are hesitant about public tools, Uber is opting for an enterprise-grade solution. This approach seeks to provide employees with powerful capabilities while maintaining the protection of sensitive company information.

How the AI agent functions

ChatGPT Work is designed to connect directly with common workplace tools used by many modern teams. According to OpenAI, the system can integrate with platforms such as Google Drive, Gmail, Google Calendar, and Slack. These connections allow the AI to act as an agent that can interact with various applications simultaneously.

Employees can use these integrations to perform a variety of professional tasks across their different software suites. For example, the tool can be used to research specific information or prepare detailed briefs for upcoming meetings. It is also capable of analyzing data sets and creating presentations for internal use.

Beyond simple content generation, the tool is built to complete entire workflows across different applications. This means it can move between tools to finish a sequence of tasks. This capability is intended to help employees manage complex projects more efficiently by automating repetitive steps.

The corporate security landscape

Uber's move stands in contrast to several other major companies that have restricted or banned public generative AI. Many of these organizations cited concerns about the protection of confidential data, source code, and general compliance. For instance, Apple restricted ChatGPT to protect its proprietary information and software plans.

Samsung Electronics famously introduced a ban on generative AI after reports surfaced that employees uploaded sensitive information to public tools. These incidents included the sharing of proprietary source code while seeking help with work tasks. Such cases have served as prominent examples of the risks associated with using public AI without adequate safeguards.

Other major institutions like JPMorgan Chase, Bank of America, and Citigroup have also placed restrictions on ChatGPT. These moves were often linked to controls over third-party software and concerns about data privacy. These actions reflect the difficulty financial institutions face when assessing public tools for work involving confidential client information.

Varied approaches to AI adoption

Different companies are taking unique paths to balance the benefits of AI with the need for data security. Goldman Sachs, for example, restricted public AI while simultaneously exploring internal generative AI applications for research and summarization. This highlights a distinction between blocking uncontrolled access and investigating AI within a managed environment.

Some companies have taken more specific approaches rather than blanket bans. Amazon warned employees against sharing confidential information with ChatGPT but directed engineers toward its own AI coding assistant, CodeWhisperer. Similarly, Accenture limited generative AI use specifically for coding and client-related work to protect professional responsibilities.

Verizon and Northrop Grumman have also blocked or restricted public tools to prevent the loss of control over customer data or defense-related information. These varied strategies show that organizations are grappling with how to vet external services before they are used for sensitive corporate work.

What comes next for enterprise AI

Uber's strategy involves more than just providing a tool; it includes approved integrations, employee training, and an internal AI skills library. This comprehensive approach suggests that successful AI adoption requires a framework of governance and education. The goal is to move from simple usage to a supervised environment where the AI's actions are monitored.

As AI tools evolve from generating text to completing multi-step work, companies will need to develop more sophisticated policies. These policies must address not only who is allowed to use the technology but also which specific systems the agent can access. Organizations will need to determine what actions the AI can perform autonomously without human intervention.

The central questions for businesses moving forward involve practicalities of data sharing and supervision. Companies must decide what information is safe to share with an agent and how to maintain oversight of its outputs. Uber's rollout serves as a case study for how large-scale corporate AI integration is being structured today.