Source: SiliconANGLE
Enterprise software is fracturing across incompatible token metering schemes—OpenAI counts tokens differently than Anthropic, which differs from open-source models—forcing companies to build custom translation layers just to understand their AI spend. The FOCUS specification group is attempting to standardize this through their billing framework, but the underlying issue runs deeper: token economics conflates compute, inference latency, and model complexity into a single unit that doesn't map cleanly to actual infrastructure costs, making budget forecasting across an AI stack difficult for most CFOs. Standardization efforts are likely to spawn a new category of enterprise software focused on AI cost management while exposing which cloud providers and AI vendors maintain opaque pricing.