AI’s Free Ride Is Over and the Tab Is Big

For the last couple of years, $10 a month bought a developer unlimited AI coding help. That deal is gone.

Microsoft’s GitHub announced that all Copilot plans will shift to usage-based billing on June 1. Fixed request allowances are out, replaced by a credit balance that depletes based on actual use. Base prices hold: Copilot Pro stays at $10 a month and Business at $19 per user. But GitHub said the previous model was no longer sustainable as infrastructure costs climbed.

Anthropic made the same call. PYMNTS reported the company began charging enterprise customers based on their AI consumption. Claude Enterprise customers now pay a flat $20 per user per month plus a variable charge tied to computing capacity used. Previously, those customers paid up to $200 per user monthly for a fixed usage allotment. Fredrik Filipsson, co-founder of Redress Compliance, a firm that helps businesses negotiate software licensing agreements, estimated the changes will double or even triple costs for heavy Claude Enterprise users, according to The Information.

Developer Behavior Shifts With the Bill

When a flat subscription covered everything, developers had no reason to hold back. They ran long sessions, tried different approaches and experimented freely. Now each extended session carries a cost, with more capable models running at higher rates.

Reaction to GitHub’s announcement was immediate. Users argued the change reduces value even where the sticker price holds. GitHub’s FAQ even included the question: “This just wiped GitHub’s value moat — why should I stay?” The company’s answer: usage-based billing aligns costs more closely to actual value and gives developers freedom to choose which models they use.

CNBC reported that Anthropic’s Claude Code surpassed $2.5 billion in annualized revenue by February, up more than 100% since the start of the year. In response, OpenAI in April rolled out a new $100-per-month Codex plan targeting the same developer audience. Running powerful AI models at that scale costs money, and neither company is willing to offer unlimited access indefinitely.

Enterprise Buyers Confront a Forecasting Problem

Traditional software costs tracked headcount. AI costs track activity. A single employee can generate thousands of AI interactions in a day. Another may trigger none. An automated process can run continuously without anyone watching the bill.

PYMNTS reported enterprise AI invoices now resemble utility bills more than software subscriptions. Charges are tied to model activity, not employee count. Finance teams built around stable annual renewals now manage a cost structure with no prior reference point.

The costs compound further down. According to PYMNTS, for every dollar spent on AI models, businesses spend $5 to $10 on integration, compliance and monitoring. The subscription was only the visible line item.

GitHub is introducing admin controls that let organizations cap spending at the company, team or individual level. Anthropic’s enterprise changes apply to accounts with more than 150 users. Both give procurement teams a mechanism for managing spend. Predicting it in advance remains a separate problem.

PYMNTS Intelligence found that more than 8 in 10 CFOs at large companies are using AI or actively considering it. AI pricing models continue to evolve as adoption scales.

The pricing pressure has a structural cause. Building and running frontier AI models requires enormous amounts of computing infrastructure. That cost compounds as usage rises. Model makers are not yet profitable at scale and usage-based pricing is one mechanism for closing that gap as adoption grows.

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