As Artificial Intelligence (AI) pilot programs conclude or mature within Higher Education Institutions (HEIs) and considerations for scaling emerge, the integration process enters the critical third phase: ongoing Monitoring and Evaluation. Transitioning from the initial implementation and data collection activities concluding Phase 2 (Chap. 12 ), this phase emphasizes the necessity of systematic, continuous assessment for AI initiatives considered “maturing” or “scaled.” These terms refer to initiatives that have moved beyond initial, contained piloting and are in advanced testing, early stages of broader rollout, or fully operational within specific institutional contexts. This chapter focuses primarily on establishing the foundational concepts and frameworks for this ongoing monitoring and evaluation; subsequent chapters will delve into the specifics of scaling (Chap. 14 ) and adaptation (Chap. 15 ). This continuous evaluation ensures that AI initiatives remain effective, ethically sound, and consistently aligned with evolving institutional goals and stakeholder values, regardless of institutional context (Weil & Forrester, 2024).