This step sets direction and ownership so AI work does not fragment into disconnected pilots. The goal is to be explicit about what AI is for, which use cases matter most, and how decisions will be made across product, data, engineering, and risk.
By the end of this step, you will have a clear foundation (core concepts and terminology), a practical AI strategy translated into AI products, and an adoption approach that helps you scale value without overwhelming teams or creating uncontrolled risk.
Step 1: Artificial Intelligence Foundations (Strategy, MLOps, GenAI, Governance)
Step 2: Define AI Strategy and Translate It into AI Products
Step 3: Choose an Adoption Approach for AI Agents (80–15–5)