US Army reinstates AI limits after troops burn through year's token supply in weeks

US Army faces AI use limits after exhausting year's supply of AI tokens

A little over a month after the Department of Defense (DOD) bragged that nearly half of its 3.5 million employees were using AI at work, members of the Army's Combat Capabilities Development Command (DEVCOM) received an email informing them that they were burning through tokens, and needed to limit use. "Although the Army CIO announced in May 2026 that they were offering unlimited tokens, by mid-June the Army CIO pool was exhausted of tokens and had to re-establish limits," the email reads. The email goes on to say that although the Army has chosen to renew token usage at "its current levels," it's unclear "if the Army CIO pool will be renewed after 1 Oct." The Army uses Ask Sage, a multimodal generative AI platform where users can run different large language models (LLMs), including Alphabet's Gemini, Meta's Llama, and OpenAI's ChatGPT. "Apparently the whole Army burned through the whole year of tokens for just one service," says an Army employee who spoke to WIRED anonymously because they were not authorized to speak to the press. Ask Sage is used by the Army to "power its enterprise LLM workspace" and is "accredited for Controlled Unclassified Information." It is also used by the DOD's Chief Digital and AI Office (CDAO) for acquisitions. According to the Army's website, Ask Sage was used to complete tasks like "reclassifying personnel descriptions, which involves defining and aligning job duties, experience and backgrounds." The Army employee says that the Army has been pushing its workers to lean into using generative AI. Employees were given an allotment of at least 200,000 tokens per month, according to emails viewed by WIRED, and were automatically allocated more if they burned through their initial allotment. Employees who had signed up for Ask Sage but were not regularly using it would receive emails encouraging them to use more of their allocated tokens. In order to use Ask Sage, the Army had access to 100,000,000 tokens as part of an annual subscription to an "enterprise pack." Tokens represent a unit of output, either in text or image, from an LLM. For the Ask Sage tool, a single token equates to about 3.7 characters, according to documents viewed by WIRED. The Defense Department burned through some 20 billion tokens per day during the 38-day Operation Epic Fury in Iran, according to Breaking Defense. The Army and DOD didn't reply to requests for comment; neither did Ask Sage. It's unclear if the tokens used by regular DOD employees are drawn from the same pool as those who might be using AI tools on classified or secret information. This hasn't stopped the Defense Department's emphasis on AI. On Monday, the Intercept reported that the Pentagon has continued to lean into AI tools, and has cut the staff at the Civilian Protection Center of Excellence, whose jobs entailed preventing civilian casualties in conflict zones. Instead, the DOD is developing an AI tool to speed up the assessments that the Center's staff would normally make. The Army is not the first eager adopter of generative AI to rethink their near unlimited use. After encouraging employees to "tokenmaxx," Meta quietly took down its leaderboard tracking token usage and is now trying to curb use. Last week, Adam Mosseri, head of Instagram at Meta, floated the idea of capping token use per engineer at the company. According to reporting from Fortune, Uber also saw its engineers burning through a year's worth of generative AI tokens in merely four months. The Army employee says they have not found the generative AI tools to be particularly useful for their work, and that when they have used the tools, they have found them to be unreliable. One model even asserted that it had completed a task that it hadn't, they say. "I think there are definitely several aspects of the bureaucracy of the US federal government that these tools might be helpful with. But an unthinking application and use is not going to result in an effective, efficient, and trustworthy rollout." This story originally appeared on wired.com.

US Army forced to reinstate limits on AI token usage after troops blew through allowances faster than expected

* The Army previously urged workers to get behind AI, offering them unlimited tokens * Limits have been reinstated by the long-term future is less certain * Iran operation saw token consumption skyrocket The US Army has reportedly been forced to reinstate limits on GenAI use after workers quickly used the full allowance of tokens early, revealing that even one of the most well-funded agencies in the world can't keep up with AI's unpredictable and rising costs. In May 2026, it was revealed that the Army would give users unlimited tokens, but by mid-June that token pool had already run dry. Now an internal email, verified by Wired, confirmed that these limits have had to be reintroduced as a result, with usage renewed at its current level for the time being. US Army struggling to keep up with AI token spend Token availability beyond October 2026 remains uncertain, though, with the Army likely worried about rising costs. "Apparently the whole Army burned through the whole year of tokens for just one service," an unnamed employee told Wired. As for the intricacies, Wired reports that an annual enterprise pack for Ask Sage, the Army's chosen AI platform, contained 100 million tokens - enough for around 200,000 tokens per employee per month. Users who exhausted their initial allocations were automatically allocated more, though, making the cap virtually pointless. To put quantities into perspective, the Defense Department reportedly used 20 billion AI tokens per day during its 38-day Operation Epic Fury in Iran. More broadly, workers have been actively encouraged to use generative AI across the breadth of their roles so that the Army could find out exactly where the tech could seriously improve productivity. Army aside, this particular case is the perfect example of how aggressive AI pushes might not always consider the impacts of cost., and with many AI vendors now shifting to unpredictable consumption-based or output-based models over flat per-seat subscriptions, it's becoming increasingly harder to predict and allocate budgets. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.