AI Frameworks for Higher Education

An Interactive Resource for Educators and Administrators

About This Resource

This interactive database provides a comprehensive overview of frameworks designed to guide the integration of artificial intelligence in higher education. As institutions navigate the rapid evolution of AI technologies—from generative AI tools like ChatGPT to comprehensive institutional AI strategies—these frameworks offer evidence-based guidance for responsible, effective, and ethical implementation.

The frameworks collected here address diverse aspects of AI integration: from institutional policy and governance to pedagogical design, from assessment strategies to AI literacy development. Whether you're developing institutional policy, redesigning curriculum, or planning professional development, these resources can inform your approach.

At a Glance

All Frameworks (13)

    Recent Publications (2023-2025)

    Framework Categories

    • Policy & Governance: Institutional-level frameworks for developing AI policies, ensuring ethical use, and establishing governance structures
    • Readiness & Implementation: Tools for assessing institutional readiness and planning strategic AI integration across systems
    • Pedagogical & Learning Design: Frameworks focused on course design, assessment strategies, and AI-augmented teaching practices
    • Literacy & Competency: Resources for developing AI literacy among students, faculty, and staff
    • Conceptual & Ethical: Theoretical frameworks addressing the philosophical and ethical dimensions of AI in education

    Key Themes Across Frameworks

    • Human-Centeredness: Consistent emphasis on AI as augmentation rather than replacement of human teaching and learning
    • Ethics & Governance: Attention to transparency, fairness, accountability, and data privacy
    • Academic Integrity: Strategies for maintaining integrity while integrating AI into assessment and learning
    • Equity & Access: Commitment to universal access and mitigation of algorithmic bias
    • Continuous Learning: Recognition that AI integration requires ongoing development and adaptation

    How to Use This Resource

    • Browse Frameworks: Explore all frameworks with filtering and search capabilities
    • Timeline View: See how frameworks have evolved from 2019 to 2025
    • Compare: Side-by-side comparison of framework characteristics
    • Feature Matrix: Visual overview of which frameworks address specific features
    • By Category: Frameworks organized by their primary focus area

    Contribute to This Resource

    Know of a framework that should be included? Help us keep this resource comprehensive and current by submitting new frameworks for consideration.

    e.g., Assessment design, Academic integrity, Training
    e.g., Ethics, Assessment, Human-centered

    Framework Development Timeline

    Framework Year Category Primary Focus Key Strength Best For Links

    Feature Coverage Matrix

    Checkmarks indicate which frameworks address specific features