Tokenomics in enterprise AI

This article explains common causes of excessive token consumption in AI services—context inflation, inappropriate use of high-end models, uncontrolled output length, and repeated automated calls—and advises organizations to adopt an operating-intent approach: segment workloads by required model quality, collect per-request token telemetry, set budgets, quotas and rate limits, and introduce approval controls for high-consumption patterns.