Exclusive: Uber cuts AI costs even as usage jumps
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After burning through its IT budget in the first quarter of the year, Uber has now stabilized its AI bills even as usage surges, the company tells Axios.
Why it matters: It's the latest example of enterprises finding creative ways to increase AI use without their bills ballooning.
State of play: Weekly agent requests at Uber have grown 9.4 times since February, but Uber's total AI spending has stayed stable since April, Uday Kiran Medisetty, distinguished engineer at Uber, wrote in a blog post.
- Using the same AI model, its cost per 1,000 requests has fallen nearly 34% from its peak in April, while its cost per session is down 52% from its June high.
- AI agents are now responsible for more than 70% of the code-change submissions at Uber.
- Uber's engineers run more than 30,000 AI-agent tasks a day, and the number of people using AI tools has more than quadrupled, per the company, yet token costs declined.
Zoom in: How did Uber reduce costs?
- Using a router, tasks are sent to the model that's best from a cost and intelligence perspective. Smaller tasks, meanwhile, go to less expensive models.
- Uber caps interactive sessions at 400,000 tokens, even when using a model that can handle up to one million tokens.
- Engineers can see the running cost of an AI session directly on their terminals.
- Uber also changed its prompt cache from five minutes to one hour because engineers often leave sessions idle for more than five minutes.
Zoom out: This comes as companies are using open-weight models more frequently, which can cut costs.
- In a post on X, Uber chief technology officer Praveen Neppalli listed experimentation with open-weight models as one of the factors driving down AI bills for the company.
- "We continuously evaluate new models and deploy the best option for each use case," he added.
Flashback: This comes after Uber's CTO said in April that Uber had blown through its 2026 AI budget in an interview with The Information.
- In August, he changed his tune, saying, "We're coming to the end of the so-called tokenmaxxing era."
The bottom line: Uber's AI experience shows how enterprise AI usage is evolving.
