The Reality of the "Tokenpocalypse" Approaching the AI Industry
Starting with Microsoft's introduction of token-based billing for GitHub Copilot, price increases are accelerating across the AI industry. This article deciphers how profitability pressure on AI companies approaching IPOs is passed on to user costs.
Microsoft’s recent announcement of a pricing system change for GitHub Copilot has sent shockwaves through the AI industry. This shift from a traditional flat-rate subscription to token-based pay-per-use pricing has been dubbed the “Tokenpocalypse” by a Reddit user. On TechCrunch’s podcast “Equity,” Anthony Ha, Karsten Colosek, and Sean O’Kane discussed what this change means for the entire AI ecosystem.
The core of the discussion is simple. AI has been heavily subsidized by investor money, but as major AI companies including Anthropic aim for IPOs one after another, pressure on profitability is inevitable. It is only a matter of time before the bill is passed on to end users and corporate customers.
The Impact of the GitHub Copilot Change
Microsoft changed GitHub Copilot’s billing from the previous flat monthly fee per user to a pay-per-use model based on the number of tokens consumed. This could lead to significantly higher costs for heavy users who frequently rely on AI code completion. On Reddit, the term “Tokenpocalypse” has been circulating, and some companies have begun imposing usage restrictions internally.
The original price of $20 per month was set with little strategic basis. Sean O’Kane points out that “ChatGPT Plus was also initially priced at $20, essentially as a random number.” The bill for that is now coming due.
Price Increases Driven by IPO Pressure
O’Kane says that when AI companies like Anthropic prepare IPO registration documents (S-1), the biggest challenge is “token-related risk factors.” With AI usage costs fluctuating rapidly, how can they describe these risks? Karsten Colosek asks, “How do you write about risks when the situation changes at a dizzying pace?”
The inference costs for AI models remain high, and the portion previously covered by investor money will now be passed on to customers. This trend is not limited to GitHub Copilot; it is expected to spread to other AI products. Companies will be forced to impose usage restrictions or revise pricing to manage costs.
Rapid Behavior Change Seen in Uber
A symbolic example is Uber’s behavior. Within just a month and a half, Uber acknowledged that it had used up more AI-related budget than expected, and soon after introduced usage restrictions and internal usage caps. O’Kane notes that this shows “how quickly companies face AI costs and are forced to pivot.”
AI labs need to reduce costs through technological progress and find a middle ground with customers’ willingness to pay. However, at this point, where that “middle ground” lies remains unclear.
Dilemma Across the Ecosystem
Karsten Colosek emphasizes the speed of the situation: “A few months ago, companies were all obsessed with ‘token maximization,’ but now the high costs are reversing that.” In other words, AI usage methods and pricing are fluid, making it extremely difficult to explain sustainable business models to investors and analysts.
Microsoft’s billing change for GitHub Copilot is just the beginning. As the IPO rush approaches, companies will be judged on how effectively they pass on their cost structures to customers or how much they can compress costs through technological innovation.
Editorial Perspective
In the short term, over the next three to six months, many AI products are likely to announce price revisions or usage restrictions. Especially for enterprise services, the introduction of pay-per-use billing or token caps will accelerate. Developers and product managers will need to estimate budgets for AI tools much more granularly than before. Microsoft’s move is seen as a trigger that will encourage similar changes from other cloud providers and AI platforms.
In the long term, the AI industry’s shift from “subscriptions to pay-per-use” mirrors the path taken by the cloud industry. However, because AI inference costs are still high and the pace of technological progress is uncertain, it will take a bit more time for prices to stabilize. Over a one-to-three-year span, demand for small, specialized models aimed at cost optimization will rise, potentially fragmenting a market that was previously dominated by giant models. Companies approaching IPOs will face the risk of going public with low gross margins.
The question from the editorial team is a point for readers to consider. How is your organization evaluating the cost of AI services and making decisions? If token-based billing is introduced for tools like GitHub Copilot or general-purpose chatbots, how do you plan to manage your budget? Also, how much do you trust the “cost reduction through technological progress” that AI labs promise? These questions are the most essential criteria for judgment in today’s AI ecosystem.
References
- TechCrunch: Is this the dawn of the Tokenpocalypse? — Published June 7, 2026
- Microsoft GitHub Copilot Official Blog (announcement on pricing change) — Related information
Frequently Asked Questions
- What exactly is the GitHub Copilot pricing change?
- It has changed from the previous flat monthly fee per user to a pay-per-use system based on the number of tokens actually consumed. This may increase costs for users who frequently use AI code completion.
- Why is the price rising across the entire AI industry?
- Many AI companies are approaching IPOs and are being forced to seek profitability, so the costs previously subsidized by investor money must be passed on to customers. Microsoft's move is seen as a precedent.
- How should companies respond to rising AI usage costs?
- Companies should monitor usage in detail, identify high-token-consumption workflows, and optimize them. Realistic measures include switching to smaller models based on use cases or setting usage caps.
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