When MIT published its State of AI in Business 2025 report, one headline dominated the conversation: 95% of organizations report no measurable return. However, leaders across those firms report sales conversion up 1.7x, customer satisfaction up 1.5x, software development productivity up 35%, manufacturing throughput up 30%, and document analysis times down 80%. And if you look at AI fluency — daily active AI users, prompts per FTE, share of workflows with AI steps, and AI-enabled cycle-time compression — these outcomes show adoption compounding, not stalling. One reason for the different take: selection bias. Their analysis draws on 52 interviews, 300 publicly disclosed initiatives, and 153 surveys at conferences that blend company sizes and contexts. Another reason: different lenses and definitions. Their conclusion centers on pilots earlier in 2025. AI fluency is an increasingly important interim metric — it captures cycle-time compression, prompts per FTE, percentage of workflows with AI steps, AI-enabled conversion, throughput, and cost to serve — and becomes a long-term driver of durable competitive advantage.