Uber and OpenAI announced an expansion of their partnership on Thursday that will put ChatGPT Work in front of Uber's entire global workforce — roughly 30,000 people. The ride-share giant previously ran the enterprise AI agent with a pilot group of 1,000 employees and is now taking it company-wide, TechCrunch reported.
From a 1,000-person pilot to the whole company For more context on this story, see our ongoing AI trends.
ChatGPT Work, introduced by OpenAI in July, is an enterprise-focused AI agent that corporate teams can deploy across everyday workflows. Uber was an early tester: the company piloted the product with 1,000 employees drawn from departments including finance, operations and product earlier this year.
One detail from that pilot stands out. According to Sumanth Sukumar, Uber's VP of engineering, about 80% of the early adopters were non-engineers. The first wave of enterprise agent adoption, at least at Uber, was not a developer story — it was operations staff, finance teams and product managers pulling an AI agent into their ordinary work.
What employees actually used it for
Sukumar told TechCrunch the pilot group applied the agent to a wide range of tasks: analyzing complex operational data to identify trends and develop recommendations, localizing training materials for different markets and languages, and building personalized interactive dashboards to manage daily work.
That list is notable for what it lacks. None of the cited use cases involve writing production code. They are the unglamorous, spreadsheet-adjacent tasks that consume hours of knowledge work — which is precisely the market OpenAI is chasing with ChatGPT Work.
Room to experiment: Uber's 'AI pods'
Uber has not settled on exactly how its 30,000 employees will use the tool, and the company is framing the rollout as deliberately open-ended.
"Our approach is to make powerful AI tools available across Uber while giving teams room to experiment," Sukumar said. As an example, he pointed to an internal program from earlier this year in which Uber paired 30 AI engineers with teams across the company 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," he said.
The approach — seed technical expertise into business teams, then let usage patterns surface organically — mirrors how many large enterprises are approaching agent deployment in 2026: less top-down mandate, more controlled experimentation with a review of what actually sticks.
What Uber isn't saying
One number was conspicuously absent from the announcement: cost. Uber did not disclose how much it is spending on the company-wide rollout. Sukumar said the company will instead track how employees use the technology, the workflows they develop, and how it helps them work more effectively — then use those outcomes to guide future AI deployment across the business.
Uber did say that OpenAI worked closely with the company on integrating the chatbot, suggesting a deeper collaboration than a standard enterprise license.
OpenAI's enterprise push
For OpenAI, the deal is another marker in a rapid enterprise expansion. Once known primarily as a consumer brand attached to ChatGPT, the company has built a loyal following among business customers while rivals have struggled to keep pace, TechCrunch noted — with Anthropic, its chief competitor, the obvious reference point.
Enterprise adoption stories like Uber's carry extra weight for OpenAI as it works to demonstrate that its business products, not just consumer subscriptions, can anchor long-term revenue. A 30,000-seat deployment at one of the world's most recognizable consumer tech companies is exactly the kind of proof point enterprise buyers look for.
It also deepens a pattern in how OpenAI is selling to big companies. Rather than shipping a fixed product and walking away, the company has embedded with early customers — Uber says OpenAI worked closely with it on integration — so that deployments double as product development. For an enterprise market still figuring out what an AI agent is for, that hands-on posture is a competitive weapon.
The bigger picture
The deployment is also a data point in the shift from AI as a chatbot to AI as a coworker. ChatGPT Work's positioning — an agent that carries tasks across applications rather than answering questions in a tab — is where OpenAI, Microsoft, Google and Anthropic have all converged. Which agent enterprises actually standardize on, and how quickly employees reshape their work around it, is becoming one of the defining enterprise software questions of the decade.
Uber, for its part, is about to generate a very large dataset on that question — 30,000 employees' worth. And the composition of its pilot, dominated by non-engineers, hints at where the next wave of agent adoption will come from: not the developers who build software, but the operations, finance and product teams who run the business. If the company-wide rollout follows the pattern of the pilot, the most instructive findings may not be about the technology at all, but about which jobs quietly reorganize themselves around it.
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