Despite heavy investments in AI, most enterprises still fail to move beyond experimentation. This article explores the “AI Paradox” — why innovation stops after the proof-of-concept stage — and how Kriv AI’s Readiness Framework helps organizations overcome gaps in data governance, model monitoring, and executive alignment. Understanding the AI Paradox Common Pitfalls: From Disconnected Data to Unclear ROI The Role of Readiness Audits in Real AI Maturity How Kriv AI Accelerate