Source: SiliconANGLE
The infrastructure economics that powered the cloud era—where you could predict compute costs and optimize gradually—no longer work when training runs cost millions and inference scales unpredictably. Enterprises are discovering that traditional FinOps playbooks (resource tagging, chargeback models, capacity planning) were built for static workloads, not for systems where a hyperparameter change can double your bill overnight. This is creating an opening for new cost-visibility vendors and forcing CFOs to demand AI teams prove ROI before scaling. The result is likely to compress spending on experimental models and favor consolidation around proven use cases.