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# Uber rolls out OpenAI's ChatGPT Work to more than 30,000 employees

**[Collections](https://daily.dev/sources/collections)** · 2 min read · 2 upvotes · 0 comments

## Summary

Uber is rolling out ChatGPT Work, OpenAI's office-task agent, to more than 30,000 employees after a 1,000-person pilot. The agent connects to Gmail, Google Drive, Google Calendar and Slack, helping staff prepare meeting briefs, build slides and analyze data. It defaults to GPT-6.1 Sol, a model priced at about a fifth of OpenAI's top model, while Uber's engineers keep using Codex for coding. Uber's CTO said in August that the 'tokenmaxxing' era of free AI spending is ending, and in July Uber laid off 10% of its customer-service team, the first time it tied layoffs to a push to use AI.

## Content

Uber is giving OpenAI's ChatGPT Work agent to more than 30,000 employees, about 30 times the size of its 1,000-person pilot. @gdb said it was great to work closely with Uber on the rollout, which brings agentic capabilities to the whole company.

## What staff get

The agent connects to Gmail, Google Drive, Google Calendar and Slack. Employees can use it to prepare meeting briefs, build slides and analyze data. It runs by default on GPT-6.1 Sol, a model priced at about a fifth of OpenAI's top model.

Engineers keep using Codex for coding. ChatGPT Work is aimed at operations, finance, marketing and product staff, backed by internal skills and training.

Uber hasn't disclosed the cost or any productivity results.

## The spending backdrop

The rollout comes after a year of tighter AI budgets at Uber. In August, CTO Praveen Neppalli Naga said the "tokenmaxxing" era of free AI spending was ending. Uber had reportedly used up its entire 2026 Claude Code budget by April.

It also follows layoffs. In July, Uber cut 10% of its customer-service team, the first time it tied layoffs to a push to use AI. A month before this rollout it cut about 3,300 roles, though the company hasn't linked ChatGPT Work to those cuts.

## A license isn't a policy

Security vendor MIND, in 2026 research with CISO ExecNet, argues that buying enterprise licenses is only the first step. Its findings:

- 74% of organizations already run approved GenAI tools like ChatGPT.
- 41% know they have shadow GenAI, such as DeepSeek or Grok.
- 70% of CISOs struggle to enforce GenAI policies, and 65% struggle to define what data is allowed.
- Only 1 in 5 AI projects meet their KPIs.

An enterprise license doesn't stop people from opening a personal ChatGPT account. MIND says security teams also need to enforce rules at the point of use and block sensitive data from unapproved tools.

With no cost or results published, it's hard to say yet whether 30,000 seats will pay off. The earlier budget fights suggest Uber is watching that closely.

## Questions this post answers

### What is ChatGPT Work and which apps does it connect to?

ChatGPT Work is OpenAI's office-task agent that connects to Gmail, Google Drive, Google Calendar and Slack. It lets employees prepare meeting briefs, build slides and analyze data. Uber rolled it out to more than 30,000 employees after piloting it with 1,000 people, running it by default on GPT-6.1 Sol, a model priced at about a fifth of OpenAI's top-tier model.

_Teams weighing office AI agents can track real enterprise rollouts like this one on daily.dev._

### Why is Uber using a cheaper GPT model for its ChatGPT Work rollout instead of OpenAI's top model?

Uber defaults ChatGPT Work to GPT-6.1 Sol, priced at about a fifth of OpenAI's top model, which fits Uber's stated push to control AI spending. Uber's CTO Praveen Neppalli Naga said in August that the 'tokenmaxxing' era of free AI spending was ending, and Uber reportedly exhausted its entire 2026 Claude Code budget by April.

_Developers budgeting AI usage at scale can follow how other companies balance cost and capability on daily.dev._

### Is Uber replacing coding work with ChatGPT Work?

No. Uber's engineers continue using Codex for coding tasks, while ChatGPT Work is deployed for general office tasks like meeting briefs, slides and data analysis across more than 30,000 employees. This split follows a 1,000-person pilot before the wider rollout.

_Engineers deciding between coding agents and office AI tools can compare real deployments on daily.dev._

## Community take

How the wider developer community reacted, aggregated from 1 discussion and 66 comments across x (as of 2026-10-27).

**TL;DR:** Reactions focus heavily on whether a company-wide rollout can actually replicate the headline 15-hours-to-30-minutes win without the embedded AI engineers who produced it, with permissions, data access, and long-term adoption flagged as the real tests.

**Sentiment:** 15% positive · 45% mixed · 40% skeptical

**The case for**

- The jump from a small pilot straight to full company-wide access, rather than staying stuck at pilot scale, is seen as a meaningful signal of commitment.
- Some expect genuinely useful internal tools to emerge from non-technical teams once they have agent access.

**The pushback**

- Many argue the impressive efficiency numbers came from a dedicated AI pod working closely with one team, not from simply handing out ChatGPT Work seats, so the gains may not generalize.
- Permission and access-control design (RBAC, OAuth scopes, audit logs, approval gates for write actions) is repeatedly raised as the real scaling risk once every employee can trigger agent actions.
- Several worry adoption will quietly stall after the initial rollout, with retention at 90 days seen as the true measure rather than seat counts.
- A few frame this as putting employee work and data onto external servers, calling it effectively outsourcing internal recordkeeping.

**By community**

- x (mixed): Replies are split between genuine curiosity about adoption/permissions mechanics and skepticism that a seat rollout alone replicates the showcased efficiency gains, alongside a fair amount of low-signal hype, jokes, and spam.

**Hottest debate:** Whether the rollout's impressive efficiency numbers are reproducible company-wide or were really the product of embedded AI specialists working with one team.

**Open questions**

- Will Uber publish adoption/retention numbers after 90 days rather than just rollout figures?
- How are agent permissions and data-access scopes managed across 30,000 employees without bypassing existing access controls?
- Which teams end up adopting and benefiting from the agents most, and is it the teams people expect?

**Highlights**

> @gdb The number in Uber's post that matters is the capital allocation one: 15 hours to 30 minutes across 150 cities. That came from an AI pod embedded with the team, not from a seat license. Giving everyone ChatGPT Work is the easy part. The pods are what don't scale.
> — [chebyte on x](https://x.com/chebyte/status/2113327865072943507)

> @gdb The best number is buried in Uber's post: one team cut a 150-city planning job from 15 hours to 30 minutes. But that team had AI engineers sitting with it. The real test is whether everyone else gets that speedup without the engineers.
> — [takezilla on x](https://x.com/takezilla/status/2113331046166970492)

> @gdb seats is the vanity metric here, the real one is buried in the replies, a 150-city planning job went from 15 hours to 30 minutes. if permissions stay locked down at $UBER most of those agents end up as expensive autocomplete by day 90
> — [EthGoldi on x](https://x.com/EthGoldi/status/2113343667201278047)

> @gdb every employee gets an agent, and every employee's work now sits on someone else's servers. uber just outsourced the filing cabinet
> — [rayvahey on x · 1 points](https://x.com/rayvahey/status/2113326317282132239)

> @gdb Company-wide agent rollouts live or die on permissions. Does ChatGPT Work inherit each employee's existing access, or does IT grant agent permissions separately?
> — [FixChatWill on x](https://x.com/FixChatWill/status/2113326638192791598)

**Source threads**

- [x](https://x.com/gdb/status/2113325885491437764) · 0 points · 66 comments

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---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#openai](https://daily.dev/tags/openai), [#chatgpt](https://daily.dev/tags/chatgpt), [#uber](https://daily.dev/tags/uber)

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