Uber is giving about 30,000 corporate employees access to OpenAI’s ChatGPT Work, extending an internal test of 1,000 staff into a company-wide office rollout that lands after Uber cut roughly 10% of its corporate workforce.
The useful number here is 30,000, because it tells you this is not a skunkworks experiment for a strategy team or a perk for engineers who already automate half their inbox. Uber and OpenAI said the tool will connect with Slack, Gmail and other workplace software so employees can research, prepare meeting briefs, build presentations, analyze data and complete workflows across apps. In plain English: less hunting, more summarizing, and a fresh invitation for middle-management tasks to justify their continued existence.
Uber’s own stated reason for the layoff round was not AI. Business Insider reported that Chief Executive Dara Khosrowshahi said the cuts, about 3,300 roles, were meant to reduce management layers and shrink the number of small teams. That matters. Companies like to drape job cuts in the language of efficiency, then drape software purchases in the language of empowerment. Sometimes both are true. They are not the same claim.
Still, the sequence is difficult to miss. Uber is cutting thousands of corporate jobs, then pushing an enterprise AI tool across the remaining office workforce. Some laid-off employees told Business Insider that AI had already been doing material parts of their work, including answering questions in Slack and drafting replies to riders and drivers. That is anecdotal evidence, not proof that this rollout replaced those specific workers. It is, however, a useful reminder that once a tool can absorb the routine half of a job, the company gets to decide whether the other half still needs a full-time person attached to it.
There is a denominator problem in a lot of AI-at-work coverage, and Uber’s announcement helps show it. A pilot for 1,000 employees can be written off as experimentation. Access for 30,000 office staff is operating policy. Compared with the 3,300 jobs eliminated, the software now touches a workforce roughly nine times larger than the one that was cut. That does not tell you how many more jobs disappear. It does tell you where management thinks the marginal productivity gains are most likely to come from.
Praveen Neppalli Naga, Uber’s chief technology officer, said in the company statement that the aim is to give employees tools to innovate, solve problems and help shape Uber’s future. Fine. Every enterprise software rollout arrives dressed for a leadership offsite. What matters more is the list of intended uses: briefing, presentation building, data analysis, workflow completion. Those are not moonshot tasks. They are the daily sediment of corporate work, exactly the sort of labor that scales poorly in headcount terms and beautifully in software demos.
Business Insider also noted that Uber cited AI in an earlier layoff round in July that targeted customer-service employees. That makes this corporate rollout less of a philosophical turn than a wider administrative one. First the frontline support jobs feel the pressure; then the office gets the tools. Capital does enjoy symmetry.
What the announcement does not prove is that Uber has found some magical route to doing more with permanently fewer people. Enterprise AI rollouts often produce a brief burst of enthusiasm, then a longer argument about quality control, security, duplication and whether the machine has simply made everyone faster at producing documents nobody needed. But if you wanted a cleaner signal of how large employers now view generative AI, this is one: not as a side project, but as standard issue.
Gabriel Fenech 
Alex de Valletta