“66% of respondents reporting their institution is currently leveraging AI, an increase from 49% year-over-year.”
Ellucian survey: adoption accelerating across higher education
An annual survey conducted by Ellucian finds higher education institutions moving quickly from experimentation to operational use of artificial intelligence. According to the survey, 66% of respondents said their institution is currently leveraging AI, up from 49% the prior year. Personal AI use among respondents is reported at near saturation: 90% say they use AI personally (an increase from 84% the previous year), and just 7% of respondents describe themselves as non-users with no intention to adopt.
Strategic planning and budget signals
Institutions are formalizing AI strategy and committing funds. Nearly half — 43% — say their institution’s strategic plan includes a focus on AI. Nearly two-thirds of executive leaders indicate their institution already allocates budget specifically for AI. The most common funding route is through a broader technology or innovation budget (48%), while another 21% are planning or exploring budget allocation for AI work.
Where leaders expect AI to deliver return
Executive leaders emphasized practical, lower‑risk, high‑return applications. The areas most frequently named as offering the greatest institutional benefits are Business & Operations (68%), Data & Analytics (59%), and Marketing, Admissions & Enrollment (51%). When asked to single out the most valuable specific AI use-case, executive leaders placed cybersecurity threat detection and response automation first, followed by revenue/expense forecasting and identifying at‑risk students.
Trust, privacy and emerging barriers
Despite growing adoption, trust and governance continue to shape institutional priorities. Data security and privacy remain the leading barrier cited at both the personal and institutional levels — 61% and 56%, respectively. New concerns are appearing: environmental impact was cited by more than one in five respondents among their top three barriers, and worries that AI could eliminate roles rose year over year from 7% to 14%.
Respondents also reported shifting confidence about AI in high‑stakes, human‑centered domains. The share who say AI does “more good than harm” for student learning declined to 45% from 55% year over year, even as perceived positive impact on academic integrity increased to 27% from 16%.
Training, governance and operational readiness
Familiarity with AI is growing, but training remains the most‑cited resource for effective adoption. The survey highlights particular operational needs: 83% of Financial Aid respondents indicate they need AI training. Governance and trust — including how to manage privacy, security and human oversight — remain central constraints as institutions deliberate where to scale AI projects.
How technologists and security teams, executive leaders, and students are responding
- Technologists and security teams: With cybersecurity threat detection and response automation named the top specific use, these teams will be primary implementers and stewards of AI tools — while simultaneously addressing the survey’s leading barriers of data security and privacy.
- Executive leaders and budget holders: Nearly two‑thirds report existing AI budget allocations and 43% have AI in strategic plans; these leaders are prioritizing lower‑risk, high‑return investments such as operations, analytics, and enrollment functions while planning governance and training commitments.
- Students, academic staff and Financial Aid offices: Confidence that AI benefits student learning has fallen, even as views of AI’s effect on academic integrity improved; Financial Aid respondents particularly signal urgent training needs, with 83% reporting they need AI training.
The Ellucian survey paints a sector in transition: institutional adoption is clearly accelerating, but so are the governance questions that will determine where AI is trusted, funded and scaled. Institutions appear to be concentrating early investments on areas that protect decision‑making and institutional resilience — business operations, analytics and cybersecurity — while flagging training, data privacy, environmental impact and workforce effects as barriers requiring policy and operational answers.