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Artificial Intelligence

Uber puts all 30,000 employees on ChatGPT Work

The ride-share giant previously deployed a much smaller pilot for ChatGPT Work but is now taking the enterprise agent company-wide.

Lucas Ropek

Publisher TechCrunch AI

Oct 22, 2026 at 4:00 PM UTC · Updated 1 天前 · 2 分钟阅读

Uber puts all 30,000 employees on ChatGPT Work
Image via TechCrunch AI

Key Signal

30,000 Uber workforce using ChatGPT

Last Updated

1 天前

翻译中…

Uber and OpenAI announced an expansion of their partnership on Thursday, with the ride-share giant telling TechCrunch that its entire global workforce — some 30,000 people — will now be using ChatGPT Work.

ChatGPT Work was introduced in July as an enterprise-focused AI agent that corporate teams could deploy for various workflows.

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Uber originally piloted ChatGPT Work with 1,000 employees earlier this year but has now scaled up its usage to the entire company.

That earlier pilot was deployed to workers from across Uber’s various departments, including finance, operations, and product. Indeed, a majority of the early adopters — some 80% — were non-engineers, Sumanth Sukumar, Uber’s VP of engineering, told TechCrunch.

“They used it for a wide range of tasks: analyzing complex data from our operations to identify trends and develop recommendations; localizing training materials for different markets and languages; and building personalized interactive dashboards to manage their daily work,” he said.

Why this matters

A company-wide deployment across Uber’s roughly 30,000-person workforce is a material enterprise adoption milestone for OpenAI and a major operational AI rollout at a global platform company. The emphasis on non-engineer use suggests generative AI tools could increasingly affect business functions beyond software development, while Uber’s outcome tracking could shape the scale and design of future deployments.

Yet while the ride-share giant is now going all in on ChatGPT, it has not settled on exactly how employees will use it. “Our approach is to make powerful AI tools available across Uber while giving teams room to experiment,” Sukumar said. “For example, earlier this year we paired 30 AI engineers with teams across Uber and gave them two weeks to automate key parts of their job. Those ‘AI pods’ showed us how much opportunity there is when you combine technical expertise with a deep understanding of a particular job.”

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