Artificial intelligence is no longer an experimental playground—it’s an operational priority. Yet many organizations struggle to move from aspiration to execution. A common starting point is an AI readiness checklist, which helps assess capabilities across data, infrastructure, talent, and governance. But a checklist alone doesn’t deliver value. What teams really need is a structured way to translate that assessment into an actionable engineering roadmap. In this guide, we’ll walk through how to transform an AI readiness checklist into a practical AI roadmap, with a strong focus on building scalable data infrastructure and aligning engineering efforts with business outcomes. Why an AI Readiness Checklist Isn’t Enough An AI readiness checklist is a diagnostic tool. It helps answer questions like: Do we have access to high-quality data? Is our infrastructure scalable and reliable? Do we have the right talent and processes? Are governance and compliance frameworks in place?…