I’m collecting input for a report on AI readiness that will cover how companies move from AI pilots to production use (including GenAI) and the blocks to that transition. I’m looking for short, specific responses from business, operations, IT, data/ML, product, security, or functional leaders who’ve been directly involved in implementing AI. All contributors will be referenced and backlinked. Please include your industry and company size. What AI-powered tools do you have in production today? Please share (a) a workflow/function where AI is used day-to-day, and (b) the #1 factor that enabled AI implementation into production (e.g., data readiness, workflow redesign, product owner, MLOps/LLMOps, executive sponsorship). What was your biggest “AI readiness” gap, and how did you address it (data quality/access, integration with legacy systems, security/privacy, compliance, etc.)? What did you change, and can you share one metric that reflects the bottleneck or improvement? How do you measure value and manage risk once AI is deployed? Please name one value metric you track and one control you rely on. If relevant: what made you scale your AI or stop it?