Student affairs: AI can deliver personalized degree planning and intervene with struggling students. In the future, it could anticipate students’ academic needs based on predictive data and past performance, and then proactively supply appropriate resources, such as additional tutoring or advising.
Institutional efficiency: AI can pull together information from multiple campus systems and use the data to guide administrative decisions such as course offerings. In the future, AI could help institutions understand local employers’ hiring needs and create curricula that prepares students to fill them.
The possibilities are both exciting and achievable, but there do exist a number of challenges that could prevent new programs from flourishing on campuses. These challenges include:
1. Accreditation and financial aid requirements should be updated to address the reimagination of academic achievement and instructional support provided by AI.
2. Privacy regulations such as FERPA need to be updated in order to address the ability of AI systems to track data and use it for predictive analytics.
3. If AI takes over some current job responsibilities such as grading and answering students’ questions, administrators and faculty members will be able to shift their focus to solving more complex problems and connecting with students on deeper levels. Administrative staff should accommodate this shift as much as possible.
The authors offer a few recommendations to help higher-ed leaders meet the opportunities and challenges AI presents in the higher ed realm:
1. Examine when to implement (short- or long-term)
2. Identify in what areas of the institution it would be most helpful
3. Determine how to protect students’ privacy while using data to help them
4. Examine what the university’s definition of success is regarding AI implementation