Learning Lab | Unlocking Change: Integrating AI and Change Management – March 2026

Part 1: March 2, 2026 | 3:00–4:30 p.m.ET
Part 2: March 5, 2026 | 3:00–4:30 p.m.ET
Part 3: March 9, 2026 | 3:00–4:30 p.m.ET
Part 4: March 12, 2026 | 3:00–4:30 p.m.ET

Overview

This comprehensive lab series offers a practical exploration of change management principles with a focus on integrating AI into everyday work in higher education. As a participant, you will learn the ADKAR model as a framework for facilitating successful change at the individual level. This model will be used to analyze driving and restraining forces affecting AI adoption. Through hands-on activities, including the AI Integration Framework, you will identify characteristics of the work, examine real-world AI use cases, and equip change agents with the skills to enhance their effectiveness in order to develop personalized action plans. By the end of the lab, you will be empowered to navigate the complexities of change management in an AI-driven environment and foster innovation and collaboration within your institution.

Learning Outcomes:

NOTE: You will be asked to complete assignments in between the Learning Lab segments that support the learning outcomes stated below. You will receive feedback and constructive critique from course facilitators.

• Analyze the Foundational Principles of Change Management: Understand the significance of adoption and usage in organizational contexts, particularly within higher education.
• Apply the ADKAR Model: Evaluate the driving and restraining forces within AI change initiatives through hands-on practical exercises.
• Create a Personalized AI Integration Plan: Utilize the AI Integration Framework to develop a tailored action plan that aligns with your specific role and responsibilities.
• Evaluate Real-World AI Use Cases: Examine five relevant AI applications that provide tactics for enhancing the effectiveness of change agents in their roles.
• Reflect on Personal Experiences: Foster a human-centered approach to navigating AI change by discussing personal challenges and insights from past change management efforts.