AI investment is now material, not experimental. Yet few enterprises clearly understand total AI program economics. Join us to explore the full cost stack of enterprise AI in 2026: infrastructure, licensing, integration, governance, talent, model operations and run-cost volatility. We examine how agentic systems affect cost predictability and how hidden integration overhead can exceed model expenses. Using aggregated budget data and deployment case analysis, we provide benchmarks for AI program scale and cost distribution. We also explore how shifting from variable labor to semi-fixed technology is changing operating leverage.