Insights

How to Prepare Your Organization for AI

AI readiness has less to do with models and more to do with workflows, data and governance. A preparation order that gets past the pilot stage.

When Fabric simplifies the estate, and when SQL Server plus Power BI is still the right answer.

What "AI-ready" requires in practice: ownership, freshness, retrieval and access control, rather than a two-year platform rebuild.

The migration order that keeps risk low: assessment, landing zone, low-risk workloads first. And the mistakes that lead to cloud regret.

The strangler-fig approach in practice: replacing the system everyone is afraid of, one piece at a time.

The roles and workflows where Copilot pays for itself, and the rollout mistakes that leave it unused.

Prompt injection, data leakage and over-trusted output: a practical security model for AI features in business software.

The savings hiding in most Azure environments, such as rightsizing, reservations and orphaned resources, and how to keep the bill down afterwards.

Ungoverned data used to produce bad reports. Now it produces confident, wrong answers. What minimum governance looks like.