Beyond tokens: How dynamic capacity management drives AI cost predictability
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The AI conversation in the boardroom has changed. By late 2025, bragging rights increasingly went to whoever could push the most tokens through their models, reflecting an assumption that more AI consumption meant more employee productivity (i.e., tokenmaxxing). In 2026, the organizations that have found real value in their early deployments are rolling them out to more teams, more use cases and more agents. At that scale, token spending is becoming a line item that finance and technology leaders need to understand, which raises a more fundamental question: What does each token an organization pays for actually contribute to the business? Answering that question has become a discipline of its own: tokenomics.
Tokenomics starts with business value per token, which depends on model choice and how the application uses the model, but quickly becomes an infrastructure question as well because utilization, hardware selection and capacity availability determine how...
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