Uber Technologies says the industry’s “tokenmaxxing” phase is winding down. The mood is getting a lot less loose: if AI costs keep climbing, companies want proof that the spending turns into real business results. CTO Praveen Neppalli Naga says teams are moving away from treating more prompts, more tokens, and heavier use of coding assistants or chatbots as automatic signs of progress. That’s the backdrop even after, according to reports, Uber had already burned through its 2026 budget for Anthropic’s Claude Code by April.
At Uber, use of advanced generative AI tools has quadrupled since the start of the year. Even so, the company says it’s bringing down cost per interaction with prompt caching, more efficient default models, and better visibility into consumption. The timing matters. Global generative AI spending is heading toward about 2.5 trillion in 2026, and according to Uber, only around 25% of 2025 projects actually hit payback targets, even though 84% of executives say returns are improving.
If you’re paying for these tools on a regular basis, this shift deserves attention, especially after Uber Technologies COO Andrew Macdonald said in May 2026 that spending trade-offs were getting harder to justify without matching productivity gains. Uber points to its internal “Agentic Pods” in finance, legal, and marketing: one planning process dropped from 15 hours to 30 minutes, and report creation fell from two days to 10 minutes. That’s where this is showing up, in model switching, semantic caching, token reduction, and smaller, cheaper models.
Author: Monique Irish Casingal
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