AI in Performance Management: Beyond the Annual Review

The annual performance review is fading from many organizations, replaced by approaches that emphasize continuous feedback, ongoing goal alignment, and richer data about how people actually work. AI plays a growing role in this shift, but the most successful implementations remain deeply human. This course gives you a calm, structured introduction to where AI fits in modern performance management. You will learn how organizations are moving past the annual review, where AI adds value, and where it can quietly create problems if applied carelessly. The course stays grounded in widely used concepts and respects the human stakes of performance work. What you'll learn: - Understand the limits of traditional performance management and the shifts under way in modern organizations - Recognize where AI adds value including goal tracking, feedback aggregation, and skill mapping - Explore the role of natural language processing in summarizing feedback and surfacing themes - Read the typical workflow from goal setting through ongoing tracking to development conversations - Identify the risks of algorithmic performance management including bias, surveillance concerns, and trust loss - Understand the integration points between performance tools, HRIS systems, and learning platforms The course begins with the changing landscape of performance management, moves through where AI fits in, and closes with the risks and responsibilities that come with these tools. Written exercises help you reflect on how each concept would apply in a real organizational context. This course is designed for HR professionals, people managers, and HR-curious leaders with no prior AI background. It is also useful for technology professionals exploring HR systems. No prerequisites are needed. The course explains every concept as it appears and treats the human side of performance as central rather than incidental.