While the deployment of AI in business and industry is widely acknowledged for its potential to improve efficiencies, decision-making, and automation, its implementation often encounters several challenges. These include integrating AI with existing systems, ensuring data quality and availability, bridging the employee skills gap, overcoming resistance to change, addressing ethical concerns, managing costs, complying with regulations, and handling ongoing maintenance and updates. In the context of higher education, however, the challenges take a different shape. Faculty members may express concerns about how AI could disrupt traditional teaching methods, necessitate changes in course delivery, and raise issues related to job security and evolving roles. To address this potential resistance, universities are increasingly developing professional development programs to help faculty integrate AI into their teaching. By adopting a human-centered approach, fostering a culture of continuous learning, providing AI literacy resources, and promoting faculty involvement in AI-related research, universities can support faculty in embracing AI more effectively. This paper presents a case study of a large, research-intensive university in the mid-Atlantic region of the U.S. and the steps it took to tackle these challenges. The paper concludes with the suggestion that by engaging faculty in a value/non-value-added task analysis of their own roles, they are more likely to better understand, appreciate, and adopt AI where it adds value.

Keywords: Education, AI, resistance to change.