AI governance must become a strategic priority for higher education
As generative artificial intelligence (AI) continues to reshape global industries, higher education faces a defining moment. According to The Chronicle of Higher Education, while 87% of campus technology leaders view AI as a transformative force, most institutions are adopting it with caution, with more than 80% moving gradually or slowly.
Our work with higher education institutions reinforces that technical deployment is but part of successful AI integration. It’s a comprehensive governance challenge that requires balancing innovation, speed, and strategy with institutional values.
Five pillars to support your AI governance foundation
Recent research and case studies from the nation’s leading research universities point to five essential pillars for an effective AI governance framework.
1. Adopt a Multi-Unit Governance Strategy
Effective governance in higher education cannot live in a silo. Research on AI governance shows multiple institutions, including 14 Big Ten universities, utilize a decentralized, multi-unit approach to manage the organizational complexity of a campus.
A successful governance structure should assign these types of explicit responsibilities:
- Information Technology (IT): Focus on security, data-sharing policies, and technical infrastructure.
- Teaching and Learning Centers: Redesign pedagogy and assessment to maintain academic integrity.
- University Libraries: Manage scholarly activity, research productivity, and proper attribution.
- Dedicated AI Centers: Act as a “one-stop shop” to consolidate fragmented guidelines for the community.
2. Elevate the Student Voice
A critical, often overlooked component of governance is the perspective of the primary stakeholders: the students. New research indicates that students are not passive recipients of AI; 96% of surveyed students already actively use tools like ChatGPT and Gemini for academic work.
Interestingly, students aren’t looking for a “free-for-all.” Instead, 94% of students believe it’s important for universities to regulate AI use. They’re calling for:
- Specific AI Courses: 81% of students support the integration of dedicated courses on AI ethics and professional applications.
- Transparent “Detective” Approaches: While students support plagiarism detection, they favor a proactive approach that prioritizes prevention and education over purely punitive sanctions.
3. Secure Your Data with “Trustworthy AI” Frameworks
Security remains a top-tier risk. Institutions can best handle these risks by leveraging existing data classification systems, categorizing information from “public” to “restricted/critical” wherever possible.
Effective governance should promote “Trustworthy AI,” defined by the National Institute of Standards and Technology (NIST) as systems that:
- Valid and Reliable: Consistently perform as intended.
- Privacy-Enhanced: Protect personally identifiable information (PII) from unauthorized exposure.
- Accountable and Transparent: Ensure AI decision-making processes are clear to the user.
4. Empower Faculty While Managing Workload
The burden of “AI-proofing” the classroom often falls on the faculty. Guidelines frequently delegate the responsibility of setting syllabus policies and detecting misuse to individual instructors. However, this practice can easily contribute to workload burnout without a solid framework.
Effective governance addresses this by providing faculty with flexible guidance, such as syllabus templates and example-based recommendations, that maintain autonomy without requiring them to reinvent the wheel for every course.
5. Moving Beyond Restrictive Rules
Governance shouldn’t just be about what students can’t do. The most effective frameworks are educative, flexible, and Socratic. They use probing questions to help the community think critically about why they’re using AI and how it impacts their long-term personal development.
From experimentation to institutional strategy
Our work with institutions shows that AI governance functions best as an ongoing conversation, not a one-time policy exercise. By prioritizing transparency and critical digital literacy, institutions can move beyond the “crisis” of AI and begin to shape the technology to fit their mission.
The goal of governance is not to stop the clock on innovation, but to ensure that as we move “full speed ahead,” we’re doing so on a foundation of integrity, security, and student success.
About the author
Curt Merlau
Vice President, Education Practice @ Resultant
Curt leads a team of outstanding education experts bringing Resultant’s mission and expertise to more places withi...
