AI Project Leadership

Traditional project management assumes you can define requirements, test against them, and call the work done, but AI initiatives don't hold still that way.
Traditional project management assumes you can define requirements, test against them, and call the work done, but AI initiatives don't hold still that way. In this course, AI Project Leadership, you'll learn to ask the right questions to judge whether an AI initiative is set up to succeed.
First, you'll explore why AI initiatives carry more uncertainty than traditional software projects, and the five factors that determine success: business case, technical build, data, governance, and people. Next, you'll discover how to apply these factors to real proposals, spotting red flags like vague outcomes, unrealistic expectations, and unassigned ownership before an initiative moves forward. Finally, you'll learn how to separate accountability from responsibility, assign decision authority, and choose where a human needs to stay in the loop based on the consequence and reversibility of a wrong output.
When you're finished with this course, you'll have the skills and knowledge of evaluating AI initiatives needed to judge whether a proposal is ready to move forward and who should own it.
Homepage

---