AI companies have swept customers onto the bandwagon by offering cheap and even free access to their AI models. But the bill is finally coming due, and the results could be ugly.

Earlier this month, Microsoft’s GitHub Copilot customers were informed that they would have to reduce their usage of the AI coding tool because of the “significant strain” placed on company servers. It also nixed free trials for new accounts, citing abuse of the system.

Now, the popular development platform is doubling down on its cost-cutting regime. On Monday, it announced that all GitHub Copilot plans will be moved to usage-based billing, charging customers based on the number of tokens their AI tasks consume.

GitHub said the change, which will go into effect on June 1, “aligns Copilot pricing with actual usage and is an important step toward a sustainable, reliable Copilot business and experience for all users.”

The company is replacing its previous “premium request units” with “GitHub AI Credits.” With the old system, users could carry out a fixed number of these intensive “premium” requests. Some requests required more units, but the actual real-world cost of performing them wasn’t factored in.

With the new system, the AI credits are directly tied to the number of tokens a request consumes. Subscribers will get an allotment of AI credits equal to the dollar amount they’re paying each month — so a user on a $10 per month plan gets $10 in monthly AI credits — and will need to pay for additional credits.

In the announcement, GitHub Product chief product officer Mario Rodriguez called the old model “no longer sustainable.” 

“A quick chat question and a multi-hour autonomous coding session can cost the user the same amount,” Rodriguez continued. “GitHub has absorbed much of the escalating inference cost behind that usage.”

The remarks are revealing. Until recently, AI companies have been happy to shoulder the costs of providing relatively cheap access to their enormously power hungry models, bringing in hundreds of millions of users into their ecosystems. 

But with the rise of AI agents and coding tools, the tasks that AIs are being asked to perform are more demanding than ever. Companies are feverishly deploying them across their workforces, encouraging employees to use the tech as much as possible. Software engineers, happy to oblige, will run multiple AI agents in the background at the same time, which can churn out code for hours on end — but accumulating significant costs on the backend.

Microsoft’s GitHub isn’t the only company heading down this route. Anthropic has repeatedly tinkered with Claude code rate limits, and recently began imposing tighter limits during peak hours. It also experimented with cutting off Claude Code access to its lowest-tier paid users, drawing alarm from users. Google imposed weekly limits on its AI coding environment Antigravity earlier this year.

Given the financial realities of the space, it’s not surprising to see AI companies start charging more. But it’ll be interesting to see how customers and business, which are already racking up huge AI bills, react to the cost changes — and what it all means for AI adoption at large.

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