Crafting Thoughtful AI Policy in Higher Education: A Guide for Institutional Leaders

• By Raffi DerSimonian, Christine Montagnino
• 03/26/25

As artificial intelligence (AI) continues to evolve at a rapid pace, education institutions find themselves at a crossroads. The integration of AI technologies presents unparalleled opportunities for enhancing teaching, learning, and administrative processes. However, it also raises critical ethical, operational, and strategic challenges.

The integration of AI into higher education is not simply a matter of technological adoption; it is an opportunity to enhance institutional mission and amplify core values. However, establishing a thoughtful AI policy that resonates with one's unique institutional mission requires a proactive approach — one that avoids simply following in the footsteps of others or adopting policies from peer institutions without careful reflection.

This article aims to guide institutional leaders through the process of crafting AI policies that are reflective of their institution's mission and future-forward. Drawing on our dual perspectives — agency leadership and institutional leadership — as well as insights from a survey of leaders across higher education, we share strategies, best practices, and an actionable framework for developing an ethical AI policy.

The Leadership Imperative: Building Trust and Driving Adoption

AI initiatives cannot succeed without strong leadership. Institutional leaders play a pivotal role in championing AI adoption by fostering trust, ensuring transparent communication, and making informed decisions. Building trust requires:

• Transparency in Communication: Leaders should articulate the "why" behind AI initiatives, addressing both opportunities and risks.
• Active Stakeholder Engagement: Regularly involve faculty, students, and staff to create a sense of shared ownership.
• Training Leadership Teams: Provide education on AI's capabilities and limitations, enabling leaders to make data-driven, ethical decisions.

Leadership training should include workshops, expert panels, and scenario planning to build confidence in navigating AI's complexities. Institutions that invest in leadership development are better positioned to drive successful, mission-aligned AI integration.

Aligning AI Policy with Broader Societal Trends

While this article focuses on higher education, institutional policies must also consider the broader societal implications of AI. Higher education institutions are uniquely positioned to:

• Prepare Students for the Future Workforce: By integrating AI into curricula, institutions can equip students with the skills needed to thrive in an AI-driven economy.
• Shape Ethical AI Use for Society: Establishing ethical AI frameworks within institutions sets a standard for responsible AI adoption across sectors.

For example, embedding AI literacy and ethical considerations into academic programs ensures that graduates understand both the potential and the pitfalls of AI, preparing them to lead responsibly in their careers.

Balancing Policy and Innovation: A Critical Tension

One of the greatest challenges in AI adoption is striking the right balance between governance and innovation. Overly rigid policies can stifle creativity, while a lack of oversight risks ethical breaches and inefficiencies. Institutions should:

• Foster a Culture of Experimentation: Encourage pilot projects that allow for controlled experimentation.
• Implement Flexible Governance Structures: Create policies that provide guardrails without hindering innovation.
• Monitor and Adapt: Use feedback from experiments to refine policies and practices.

By framing governance as an enabler rather than a constraint, institutions can cultivate an environment where innovation thrives alongside accountability.

Assessing Effectiveness: KPIs for AI Initiatives

To ensure that AI initiatives are achieving their intended outcomes, institutions must establish clear metrics for success. Key performance indicators (KPIs) may include:

• Educational Outcomes: Improved retention rates, higher graduation rates, or enhanced learning outcomes.
  
• Operational Efficiency: Reduced administrative workload or faster service delivery.
  
• Ethical Compliance: Reduction in algorithmic bias and increased data transparency.

For example, a university's marketing team might track engagement rates for AI-driven personalized campaigns, while the advising office measures improvements in student satisfaction through AI-powered support tools. Regularly reviewing these metrics allows institutions to make data-informed adjustments.

Steps for Crafting a Thoughtful AI Policy

Drawing on survey insights, research, and our collective experience, we propose a step-by-step framework for developing an institutional AI policy:

1. Define the Purpose: Clearly articulate how AI will support your institution's mission, vision, and core values. Actionable Tip: Create a mission statement for AI use that aligns with institutional goals.
2. Engage Stakeholders: Involve faculty, students, administrators, and other stakeholders from the outset. Actionable Tip: Develop a stakeholder engagement plan with regular feedback sessions.
3. Establish Ethical Guidelines: Develop principles that address privacy, fairness, and accountability. Actionable Tip: Draft an ethical AI charter and solicit campuswide feedback.
4. Create Governance Structures: Form committees or task forces to oversee AI implementation. Actionable Tip: Assign a dedicated AI governance team to monitor adherence to policies.
5. Pilot and Evaluate: Test AI applications in low-risk areas and gather feedback to refine strategies. Actionable Tip: Evaluate outcomes against predefined KPIs.
6. Communicate Transparently: Share information about AI initiatives, including successes and challenges. Actionable Tip: Develop a communication plan with regular updates and open forums.
7. Continuously Monitor and Improve: Regularly assess AI's impact and make adjustments as needed. Actionable Tip: Implement an annual review cycle for AI policies.

Top 10 AI Policies from Leading Institutions

To provide further guidance, we have curated a list of exemplary AI policies from leading colleges and universities that have successfully implemented thoughtful and mission-driven AI frameworks. These policies serve as models for institutions seeking to craft or refine their own AI strategies:

• Stanford University: Focuses on transparency and accountability in AI decision-making, including a public ethics review board.
• Massachusetts Institute of Technology (MIT): Implements regular AI ethics audits and a governance committee dedicated to ethical AI deployment.
• Harvard University: Emphasizes stakeholder engagement, including student and faculty advisory panels to guide AI use.
• University of California, Berkeley: Uses AI to enhance student support services, with clear policies on data privacy and informed consent.
• Arizona State University: Employs AI in adaptive learning platforms with a focus on personalized education pathways.
• University of Toronto: Developed a comprehensive AI ethics framework that addresses bias, fairness, and data transparency.
• University of Michigan: Has an AI oversight committee responsible for evaluating new AI initiatives and ensuring alignment with institutional values.
• Carnegie Mellon University: Prioritizes interdisciplinary collaboration in AI projects, involving stakeholders from various academic departments.
• University of Edinburgh: Created a public-facing AI charter that details ethical principles, stakeholder responsibilities, and governance mechanisms.
• Champlain College Online: Focuses on personalized learning and career relevance, using AI to support diverse student populations in an online environment.

Leading with Vision and Integrity

The integration of AI into higher education holds the promise of transformative benefits, from personalized learning to enhanced administrative efficiency. However, to fully realize these benefits, institutions must approach AI adoption thoughtfully, with a focus on mission alignment, ethical considerations, and stakeholder engagement.

By leading with intent, involving diverse voices, and establishing a strong ethical foundation, institutions can harness AI's potential in ways that are innovative, responsible, and mission-driven. We encourage institutional leaders to take a proactive stance — to lead rather than follow — and to craft AI policies that reflect the unique values of their communities.

Next Steps

If you are inspired to take action, consider the following:

• Conduct a Readiness Assessment: Evaluate your institution's current capabilities and identify gaps in AI adoption.
• Facilitate Cross-Functional Workshops: Bring together stakeholders to co-create an AI policy framework.
• Engage Experts: Partner with thought leaders in AI ethics and education to refine your strategies.

We welcome opportunities to collaborate on workshops, policy frameworks, and best practices to support this vital work.