Uber rolls out ChatGPT Work to all 30,000 employees

Uber has made ChatGPT Work available to its entire global workforce of more than 30,000 employees, starting today. The rollout follows a pilot that involved 1,000 staff across finance, operations, and product teams earlier this year. Uber says the AI agent will help workers automate multi‑step tasks, from data analysis to creating presentations, using tools they already rely on such as Google Drive, Gmail and Slack.

Key facts

Uber’s AI rollout reaches over 30,000 employees worldwide.
The expansion builds on a pilot that included 1,000 users, 80% of whom were non‑engineers.
ChatGPT Work integrates with Google Workspace, Slack and other daily‑use applications.
The platform runs on OpenAI’s latest frontier models, including GPT‑6.1 Sol, balancing performance and cost.
Uber will monitor usage patterns and outcomes to guide future AI deployments.

Why it matters

Providing a company‑wide AI assistant signals a shift from experimental pilots to mainstream adoption of generative AI in large enterprises. By embedding ChatGPT Work into everyday tools, Uber aims to reduce manual effort, speed up decision‑making and free up staff for higher‑value activities. According to Sumanth Sukumar, Uber’s VP of engineering, the early pilot showed that even employees without a technical background could leverage the agent for complex data analysis, localization of training material and the creation of interactive dashboards. This democratization of AI could set a benchmark for other firms seeking to scale AI assistance across diverse functions.

How ChatGPT Work is used at Uber

Use case	Typical workflow	Benefit
Data analysis	Employee asks the agent to pull operational metrics from internal databases, generate visualizations, and summarize trends.	Faster insight generation, reduced spreadsheet time
Meeting preparation	The AI drafts briefing notes, extracts relevant emails, and builds slide decks from Google Slides.	Consistent, polished materials with less manual effort
Localization	The agent adapts training content to local languages and market nuances.	Faster rollout of region‑specific programs
Routine admin	Scheduling meetings, drafting routine emails, updating calendars.	Saves minutes on repetitive tasks

The tool also supports multimodal capabilities such as voice commands and image generation, allowing teams to choose the most suitable model for a given task. Uber’s internal AI skills library and approved integrations ensure that employees have guidance on best practices and security compliance.

Background on the partnership

OpenAI launched ChatGPT Work in July 2026 as part of its enterprise offering, positioning it as an “agentic platform” that can execute multi‑step processes across applications. Uber was one of the first large corporations to test the service, enrolling 1,000 employees from a cross‑section of departments. During the pilot, the company observed that roughly four‑fifths of users were not engineers, underscoring the tool’s accessibility. OpenAI’s August update added a web‑navigation feature that lets the AI log into sites, fill forms and handle authentication without exposing passwords to the model, a safety measure highlighted by the developer.

The partnership aligns with Uber’s broader AI strategy, which includes using OpenAI’s Codex for code generation and exploring custom AI pods that pair engineers with business teams to automate specific workflows. While Uber has not disclosed the financial outlay for the rollout, the company emphasized that it will track adoption metrics and performance improvements to inform future AI investments.

What’s next

Uber plans to publish periodic reports on adoption rates, workflow categories and measurable efficiency gains.
OpenAI will continue to roll out new model versions and multimodal features, which Uber can integrate into its internal tools.
The company’s AI skills library will be expanded with use‑case templates, helping non‑technical staff discover new ways to apply the assistant.
Uber’s “AI pods” experiment may be scaled, pairing more engineers with business units to co‑design automated solutions.