GitHub Copilot a token: What changes for development teams

Copilot's flat-rate model is over: what has changed

Until a few months ago, GitHub Copilot offered a fixed monthly subscription. Developers paid a predictable fee and used the tool without significant operational limitations. However, Microsoft has decided to change course substantially.

The new model introduces the token billing. In practice, every request sent to the AI model consumes a token quota. Consequently, the more the team uses Copilot—for autocompletion, function generation, code review—the higher the bill grows.

According to reports by TechCrunch, the community's reaction was immediate. Phrases like “What a joke” They circulate in technical forums. Therefore, the discontent is not marginal: it affects teams of all sizes, from freelancers to structured software houses.

Why is the developer community alarmed?

The problem is not just economic. It is structural. A consumption model introduces imprevedibilità nei budget. For a team of five developers using Copilot daily, estimating the monthly cost becomes a complex exercise.

Furthermore, token-based billing penalizes more intensive use cases. For example, those who use Copilot to generate automated tests or inline documentation consume massive amounts of tokens. Conversely, those who use it only for sporadic autocompletion might even save money compared to the old flat-rate.

So, the new model creates a clear fork. On one hand, light users who pay less. On the other, power users and structured teams who see costs rise. In particular, tech SMEs — often with limited IT budgets — almost always fall into the second category.

According to Gartner, the adoption of AI tools for software development is projected to grow by 40% by 2025. Therefore, a price change for such a widely used tool has systemic impacts, not just individual ones.

The concrete impact on Italian tech SMEs

Italian SMEs operating in the tech sector or with in-house development teams face a non-trivial decision. In fact, many of them have integrated Copilot into their workflows over the past two years. Abandoning it is not straightforward.

However, the risk of uncontrolled costs is real. A team of ten developers using Copilot for eight hours a day could generate monthly expenses that are difficult to justify in a small and medium-sized enterprise budget. Therefore, assessing alternatives has become urgent.

Among the costs to consider are:

• Tokens consumed for autocompletion: the most used function, but also the one that generates the most traffic to the models.
• Token per chat and extended generationAI dialogue sessions consume significant quotas.
• Token per review and refactoringAdvanced functions with high per-request consumption.
• Costs of integration with different IDEsSome configurations increase the number of API calls.

In addition to this, the hidden cost of Billing Management. Monitoring token consumption requires attention and additional tools. For an SME without a dedicated DevOps team, this represents a real operational burden.

Alternatives that are gaining ground

Dissatisfaction with Copilot is accelerating the adoption of alternative tools. Some are open source, others are commercial with more stable pricing models. Right now, the market offers concrete options.

Cursor It is one of the most cited AI-native editors as an alternative. It offers fixed quota plans and a comparable development experience. Similarly, Codeium e Tabnine they maintain freemium models with predictable price tiers.

For teams that prefer self-hosted solutions, Continue.dev with local models (like Ollama) represents a zero-cost option per token, but with infrastructural investment. Therefore, the choice depends on the team's technical profile and operational risk tolerance.

According to Harvard Business Review, companies that diversify their AI stack reduce their dependence on single vendors and improve the resilience of their technology budgets. Therefore, this is not just an emotional reaction to a pricing change: it is a sensible strategy.

What Microsoft hasn't clearly communicated

One element that strongly emerges from the online debate is the lack of upfront transparency. The transition to token-based billing was not accompanied by clear communication regarding expected costs for the most common usage profiles.

In fact, many developers discovered the change by reading release notes or community posts, not through a direct notification. Despite this, Microsoft published technical documentation on the new system. However, technical documentation does not replace transparent business communication to existing customers.

This aspect is relevant for Italian SMEs purchasing Copilot through Microsoft 365 or Azure licenses. In some cases, the pricing change is part of an active contract. Therefore, it is advisable to check the specific terms of your contract with your Microsoft reseller.

What to do in the coming weeks: an operational reading

In the face of this scenario, we at SHM Studio we suggest a structured three-phase approach. First, it is necessary measure current consumption. Without real data on Copilot usage within your team, any economic assessment is an approximation.

Following this, you can proceed with a Simulation of future costs Based on the new pricing model, GitHub provides tools to estimate token consumption. It's useful to apply them to your team's historical data for a realistic projection.

Finally, it's worth conducting a comparative evaluation with at least two alternatives. It’s not necessarily about abandoning Copilot: in some cases, the new model might prove convenient. However, having an evaluated alternative reduces dependence and increases bargaining power.

For SMEs looking to deepen the integration of AI tools into their digital processes, our team is available for dedicated consulting. You can explore our expertise on AI services or contact us directly at Contact Us.

Prospects: Towards a More Competitive AI Coding Tools Market

GitHub Copilot's change of course could have an unexpected effect: stimulating competition. Indeed, when the market leader introduces a model perceived as less favorable, competitors benefit directly.

In the short term, growth is expected in the adoption of alternative tools. In the medium term, Microsoft is likely to review some aspects of its pricing in response to community feedback. Similarly, other providers—such as Anthropic with Claude for code or Google with Gemini Code Assist—may accelerate their competitive offerings.

For Italian tech SMEs, this is a favorable moment to re-evaluate their development stack. Not as an emotional reaction, but as a strategic exercise. The choice of AI tools impacts team productivity, code quality, and long-term cost sustainability.

Those who manage or supervise development teams can also find useful insights in our analyses on Digital transformation and AI, or to further explore how AI integrates with strategies digital marketing e web development for Italian SMEs.