Enterprise AI Strategy & Adoption

About this course

This course provides a rigorous, non-technical framework for designing, governing, and executing enterprise AI strategy beyond pilots and experimentation. It focuses on how organizations should decide where AI belongs, how it should be adopted, and why many AI initiatives fail despite strong technology and vendor promises.

Participants learn to treat AI adoption as an organizational transformation problem rather than a tooling decision. The course explains how AI maturity evolves, why strategy must precede use cases, and how misaligned incentives, unclear ownership, and poor evaluation frameworks undermine value creation. Emphasis is placed on system-level thinking, cross-functional coordination, and long-term operational reality.

Rather than promoting aggressive automation or blanket adoption, the course builds durable mental models for making disciplined AI decisions. Participants examine buy vs build vs partner tradeoffs, vendor dependency risks, organizational readiness gaps, and the human factors that determine whether AI initiatives scale or stall.

This course is designed for leaders, strategy teams, product owners, legal and compliance professionals, and managers responsible for approving, prioritizing, or overseeing AI initiatives across the organization, without writing code or understanding mathematics.