The dollar AI deals ended in a meter, and meters need ceilings
Six weeks before GSA’s nominal-price AI offers expired, agencies had no successor terms. Usage pricing was the likely replacement, which moves the hard decisions to budget execution: how to fund a meter, who runs it, and how to keep alternatives.
Looking Back revisits one week at a time, from January 2020 to today, and asks what it meant for the banks, health systems and public agencies we serve. The series was written in 2026, with the benefit of hindsight, and each article says which week it looks back on.
The week
In August 2025, GSA announced OneGov agreements that gave federal agencies enterprise generative AI tools at nominal prices for a year. OpenAI offered ChatGPT Enterprise for $1 per agency, Anthropic offered Claude for $1, and Google offered Gemini for Government for $0.47 per agency. By mid-August 2026, reseller listings showed the three offers expiring on September 30. GSA had not named what would follow. Reporting at the time noted that some subscriptions would not renew automatically, and that renewal for at least one product would be priced per user. The outgoing federal CIO had said months earlier that prices would not stay at a dollar and that renewal pricing would draw on usage data. GSA later put the number of federal employees with access through its AI agreements at roughly 3.5 million.
Earlier in this series we argued that the dollar price never decided adoption. What decided it was a security authorization, a ruling on which data could go in, and an owner for records and oversight. A year later, price came back in a different form. Every signal in August pointed toward usage-based or per-seat pricing, and usage pricing changes who controls spending. Under a flat fee, a contracting officer fixes the cost at award. Under a meter, the cost is set by thousands of employees each time they send a prompt, upload a file or run an agent.
That shift raised three decisions that agencies needed to settle before September 30, and each belongs to a different office. The first is how to fund a meter, which belongs to the chief financial officer. The second is who gets to run it, which belongs to the CIO and program leaders. The third is how to keep alternatives, which belongs to acquisition and records staff. Together they cover what changes when a fixed-price tool becomes a consumption service.
Funding a meter
Federal agencies cannot obligate money they do not have. The Antideficiency Act forbids obligations in excess of available appropriations, and open-ended consumption pricing sits awkwardly with that rule. Cloud computing has dealt with the same problem for a decade, and the answers carry over. An order needs a funded ceiling, a not-to-exceed amount, and a way to see spending against it in close to real time.
In practice that means three controls. The order should cap obligations at a funded amount, with modifications to add funds as use grows. The vendor’s administrative console, or a billing feed, should report consumption by bureau or office at least weekly. And someone should own a burn-rate threshold that triggers a decision before the ceiling is reached, such as throttling, re-prioritizing or adding funds. Agencies running under a continuing resolution have extra reason to watch the burn, since they may be funding a new cost at the prior year’s rate. Budget and appropriations law staff should review the structure before the first order.
Model choice is also a cost decision under a meter. Token prices differ widely between a provider’s largest and smallest models, so the same request can cost many times more on one than the other. Setting a default model for routine work, with the more capable models available on request, is one of the cheapest controls an agency has.
Deciding who runs it
A nominal fee rewarded broad enablement. Giving a tool to every employee cost nothing extra, so many agencies did. A meter reverses that logic. Light users cost little, while heavy users, long documents and agentic workflows can cost a great deal. The access model has to change accordingly.
Agencies can sort users into tiers based on what the first year showed. General staff might keep access to a basic model with a monthly allowance. Teams with measured use cases, such as drafting correspondence, summarizing case files or coding, get higher limits and more capable models. Pilots of agent features run under separate budgets with their own ceilings. Usage data from the first year is the raw material for this. Most enterprise consoles show active users, volume and feature use. Agencies that exported and kept that data could size tiers from evidence instead of guesswork.
Chargeback matters too. If a department funds the order centrally, bureaus have no reason to economize. Showing each bureau its own consumption, even without billing it, changes behavior. It also gives the chief AI officer a basis for reporting value by program rather than in aggregate. Cost per active user and cost per measured use case, reviewed monthly, are the two numbers a budget officer will ask for first.
Keeping alternatives
The three offers did not have to end the same way, and agencies were better placed if they could move between them. Two kinds of portability decide that. The first is technical. Workflows built through a model-agnostic layer, such as GSA’s USAi evaluation platform or an agency’s own gateway, can be pointed at another model when prices change. Custom assistants built inside one vendor’s interface usually cannot. An inventory of what staff built in the first year, and where, shows how locked in the agency is.
The second kind is records. Conversation histories, uploaded files and custom configurations may be federal records, depending on content. An agency needs to know how to export and retain them if it stops paying, or narrows access, at the end of a term. That should be tested with the records officer before the decision, because retention after a subscription ends varies by product and by contract.
With exports and a gateway in place, the September decision became a real choice. An agency could renew broadly, narrow use to proven cases, move some workloads to another provider, or compete the requirement. Without them, the only realistic option was to accept whatever terms arrived.
With hindsight
The terms did arrive, in different shapes. On September 10, GSA announced a 27-month OneGov offer for OpenAI’s models, effective October 1 and running through 2028. It replaced the flat fee with a 50 percent discount on token-based usage, with no platform fee, no minimum order and no spend commitment. It also opened to state, local and tribal governments. By the end of September, Anthropic’s and Google’s offers had been extended into late October and mid-November. GSA said it would renew agreements where appropriate. The design confirmed the meter, and the absence of a spend commitment leaves budget control entirely with each agency. Published pricing does not tell us how much agencies will spend. That will depend on the ceilings, tiers and exits each one set up, and we have not seen consolidated figures.