Uber Rolls Out ChatGPT Work to Entire 30,000-Employee Global Workforce

Uber Scales ChatGPT Work Deployment Across Global Workforce

Uber and OpenAI announced an expansion of their partnership, with the ride-share company deploying ChatGPT Work to its entire global workforce of approximately 30,000 employees1

1

2

2

. This company-wide rollout follows a successful pilot program with 1,000 employees earlier this year, marking a significant milestone in enterprise AI adoption1

1

.

ChatGPT Work, introduced by OpenAI in July, is an enterprise-focused AI agent designed to handle complex, multi-step office tasks and deliver finished work3

3

. The platform integrates with essential workplace tools including Gmail, Google Drive, Google Calendar, and Slack, enabling employees to prepare meeting briefs, build presentations, analyze data, and complete workflows across applications2

2

3

3

.

Pilot Program Demonstrates Broad Appeal Beyond Engineering

The initial pilot program revealed compelling insights about AI adoption patterns within Uber. Sumanth Sukumar, Uber's VP of engineering, disclosed that 80% of early adopters were non-engineers, spanning departments including finance, operations, and product teams1

1

. These employees leveraged the tool for analyzing complex data from operations to identify trends and develop recommendations, localizing training materials for different markets and languages, and building personalized interactive dashboards to manage daily work1

1

.

Uber's approach to AI deployment emphasizes experimentation and innovation. Earlier this year, the company paired 30 AI engineers with teams across Uber in what they called "AI pods," giving them two weeks to automate key parts of their jobs1

1

. These pods demonstrated significant opportunities when combining technical expertise with deep understanding of specific job functions, informing the broader deployment strategy1

1

.

Strategic Cost Management Through GPT-6.1 Sol Model

By default, ChatGPT Work will run on GPT-6.1 Sol, a model OpenAI released at approximately one-fifth the price of its top model2

2

. This deployment comes as Uber actively manages AI spending. In August, Uber's Chief Technology Officer Praveen Neppalli Naga declared the era of "tokenmaxxing"—spending freely on AI—was ending2

2

. Reports indicated Uber had exhausted its entire 2026 budget for Anthropic's Claude Code by April, highlighting the financial pressures of AI adoption2

2

.

While Uber's developers and software engineering teams will continue using Codex, OpenAI's coding tool, for software development and coding workflows, the broader workforce will benefit from the cost-efficient GPT-6.1 Sol model for automating workflows and problem-solving2

2

3

3

.

AI Deployment Linked to Workforce Transformation

Uber has also tied AI adoption to workforce restructuring. In July, the company laid off 10% of its customer-service team, marking the first time it explicitly linked job cuts to its AI push2

2

. This development signals how AI deployment is reshaping organizational structures and job functions across the company.

Neppalli Naga emphasized the strategic importance of this rollout: "As AI transforms how we work, we want to give everyone the tools to innovate, solve problems and help shape Uber's future. Rolling out ChatGPT Work across the company is an exciting step toward that ambition"2

2

3

3

.

OpenAI's Enterprise Business Growth and Competitive Positioning

This partnership expansion strengthens OpenAI's enterprise business growth trajectory. Greg Brockman, OpenAI's President and Co-Founder, noted that teams across Uber can now tap into OpenAI's portfolio of frontier models and agents to take on more complex work and connect tools they use daily3

3

. OpenAI's enterprise business is driving significant revenue gains, with annualized revenue expected to reach at least $70 billion by year-end, up from $50 billion at the end of September3

3

.

Uber and OpenAI plan to share insights on how staff use the agent and what results it brings as the rollout progresses2

2

. Sukumar indicated the company will track employee usage patterns, the types of workflows developed, and effectiveness metrics to guide future AI deployment decisions across the business1

1

.