Key points
- Uber is rolling out ChatGPT Work to its entire global workforce, about 30,000 people, according to TechCrunch.
- The rollout follows a pilot with 1,000 employees across finance, operations and product; about 80% of early adopters were non-engineers.
- Pilot uses included trend analysis of operations data, localizing training materials, and building personalized dashboards.
- Uber did not disclose spending and says it will track usage and workflows to guide future AI deployment.
Why it matters for marketers: A 30,000-person rollout led by non-engineers shows agents moving into everyday business work, including localization and reporting tasks that marketing and content teams handle.
Uber and OpenAI announced an expanded partnership on Thursday, and Uber told TechCrunch that its whole global workforce, roughly 30,000 people, will now use ChatGPT Work. OpenAI introduced the product in July as an enterprise-focused AI agent that teams can deploy across workflows.
The company started with a pilot of 1,000 employees earlier this year, drawn from departments including finance, operations and product. Sumanth Sukumar, Uber's VP of engineering, said about 80% of those early users were non-engineers. They used the tool to analyze operations data for trends, localize training materials for different markets and languages, and build personalized dashboards for daily work.
For marketers and content teams, the pilot's use cases are familiar ones: data analysis, localization and reporting. The fact that most early adopters were not technical suggests agent tools are being judged on everyday business tasks rather than engineering work alone.
Uber has not fixed a single way for staff to use the tool. Sukumar described an approach of making AI broadly available while leaving room for teams to experiment, and pointed to earlier "AI pods" in which 30 AI engineers worked with teams for two weeks to automate parts of their jobs. Uber did not disclose what the rollout costs.
What to watch: Uber says it will study how employees use the tool and which workflows they build, then use those findings to guide wider AI deployment. Those results could offer a useful template for teams planning their own agent rollouts.
Sources
This brief is our own summary. Read the full reporting at the source.