Apple is reportedly cutting budgets for its internal AI usage
Apple is reportedly cutting budgets for its internal AI usage
Apple has reduced the daily AI spending limit for its engineering team from 300 dollars to 200 dollars, and plans to further cut it to 100 dollars, with external engineering budgets possibly as low as 25 dollars. Previously, the company had encouraged employees to overuse AI for efficiency, but later shifted to a more frugal approach due to cost issues.
Same story2 other outlets also reported this
- ITHome · AI··First
Apple tightens employee AI usage budget: daily limit for some engineers decreases by 33%, potentially dropping further to 100 dollars.
- 36Kr · AI··+31 min
Apple reduces AI usage budget for employees, daily limits for some engineering teams may drop to 100 dollars
Adds:36Kr mentions the initial reduction is from 300 dollars to 200 dollars.
- TechCrunch · AI··+2 h 19 min·Reading now
It is reported that Apple has cut its internal AI usage budget
In order of publication · later reports are added as they appear · Compared by AI from each outlet’s title and summary
In Brief
Posted:
5:26 PM PST · November 4, 2026
Apple is cutting the daily amount its engineering teams can spend on AI, Bloomberg reported Wednesday. It’s a big change for a company that has worked to integrate the technology into its engineering processes.
In October, Apple lowered the daily AI spending cap for its engineering teams, decreasing it from $300 to $200, the outlet reported. And more cuts are in the works, with some allowances falling to $100 a day, sources tell Bloomberg. Outside engineering, Apple is reportedly weighing a daily limit as low as $25 a day.
TechCrunch has reached out to Apple for comment.
Earlier this year, a tsunami of tokenmaxxing took hold, with companies pushing staff to use AI as much as possible in the name of vaguely defined efficiency gains. The frenzy was short-lived, however, as bills for said tokens came due, and companies decided that token rationing might be a more fiscally sensible approach.
Concerns persist about an apparent gap between what AI costs to build and run and the (often unclear) productivity gains the technology is suppose to generate.
Source: TechCrunch · AI · techcrunch.com