EDUCAUSE AI Landscape Study navigates the AI revolution in Higher Education

Strategic Planning and Readiness:

• Most institutions are working on AI-related strategy. Only 11% of respondents said that nobody at their institution is working on AI-related strategy.
• Institutions are concerned about falling behind. Most respondents said that the rise of student use of AI in their courses and the risks of inappropriate use of AI (73% and 68%, respectively) were primary motivators for AI-related strategic planning.
• The goals of AI-related strategic planning are primarily related to supporting students. The three highest-ranking goals of AI-related strategic planning are preparing students for the future workforce, exploring new methods of teaching and learning, and improving higher education for the greater good (selected by 64%, 63%, and 41% of respondents, respectively). Further, most respondents said that their AI-related strategy is somewhat or to a great extent focused on boosting educational experiences and student services (76%).
• Institutions are primarily operationalizing these goals by providing training for faculty, staff, and students (56%, 49%, and 39%, respectively).

Strategic Leaders and Partners:

• Leaders are cautiously optimistic about AI. Most executive respondents reported that leaders at their institution are either approaching AI with a mix of caution and enthusiasm or feel optimistic about AI (52% and 29%, respectively).
• Stakeholders lack awareness of each other’s AI-related sentiments, strategy, and policy across their institutions, likely a result of institutional silos.
• More than half of respondents (56%) indicated that they have personally been given responsibilities related to AI strategy.
• Most respondents indicated that all functional areas are at least somewhat responsible for AI-related strategy
• More than half of respondents (57%) indicated that either their institution is not working with third-party partners to develop AI strategy or they don’t know whether their institution is working with third-party partners to develop AI strategy.

Policies and Procedures:

• AI is making the biggest impact on policies for teaching and learning, technology, and cybersecurity and data privacy (reported by 95%, 79%, and 72% of respondents, respectively, as “already impacted” or “soon to be impacted”).
• Academic integrity is still top of mind. A majority of respondents (78%) indicated that AI has impacted academic integrity.
• Data governance practices are shifting in response to AI. Nearly half of executive leaders (47%) said that their institution is preparing data to be AI-ready.
• Data privacy and security are central concerns. Privacy and security professionals are most concerned with data security (82%), compliance with federal regulations (74%), ethical data governance (56%), compliance with local regulations (56%), and the impacts of biases in data (52%).
• Only 18% of respondents said their AI-related policies are somewhat or extremely restrictive—for example, banning student or faculty use.

Workforce and the Future of AI in Higher Education:

• Although many faculty and staff are being tasked with AI-related job duties, few job roles have been formally created or restructured to accommodate such duties. More than half of respondents (56%) reported that they have been personally given AI-related responsibilities, but few respondents were aware of new jobs being created or existing jobs being formally modified (11% and 14%, respectively).
• Stakeholders feel that there are some appropriate uses for AI-powered technologies in higher education: personalized student support; acting as a teaching, research, or administrative assistant; conducting learning analytics; and supporting digital literacy training.
• Respondents also identified inappropriate uses, such as using outputs without human oversight, failing to disclose or cite AI as a resource, and failing to properly protect data security and individuals’ privacy.