Key points:
- AI presents unprecedented opportunities, but its adoption across remains uneven and fragmented
- The 5 dimensions of AI literacy
- Why agentic AI matters now more than ever
- For more news on AI readiness, visit eCN’s AI in Education hub
A new framework from the Digital Education Council 2025 AI Working Group provides a shared structure for higher education institutions to assess their current state of AI readiness.
The Ten Dimension AI Readiness Framework was developed with input from 27 universities across 17 countries and offers a unified framework for higher education institutions to comprehensively evaluate their current AI readiness across 10 key dimensions.
Institutions continue to grapple with many of the same challenges that emerged during early AI implementations–misalignment with curricular goals, gaps in faculty training, and systemic obstacles to adoption.
As AI applications grow in scale and complexity, addressing these issues demands a coordinated, strategic response rather than isolated tech-driven efforts. In response to this need, the Digital Education Council launched the Thematic Working Group on AI and Education in January 2024. This group was tasked with creating a robust AI Readiness Framework to help institutions evaluate and strengthen their preparedness for AI integration.
Through a series of discussions and collaborative analyses, several recurring themes emerged, forming the basis of the Ten Dimension AI Readiness Framework, which is built to help institutions craft a well-rounded AI strategy that goes beyond a narrow focus on generative AI. Although GenAI has garnered significant public and academic interest, long-term, effective AI adoption requires attention to ethical governance, predictive analytics, AI-driven student support, and data-informed institutional decision-making. Relying solely on a GenAI-centric approach risks overlooking the wider potential of AI to transform teaching, research, and administrative functions in meaningful ways.
To tackle these challenges, the Ten Dimension AI Readiness Framework offers a structured, multifaceted approach rooted in four core principles:
1. Resilience: Build capacity to withstand challenges and adapt to AI advancements
2. Transformation: Leverage AI to drive meaningful innovation in teaching, research, and operations
3. Adaptability: Stay flexible by responding to emerging technologies and industry needs
4. Community: Cultivate an ecosystem of shared responsibility, collaboration, and co-creation among internal and external stakeholders
The Digital Education Council 10 dimensions of AI readiness includes:
1. Strategic Alignment: The degree to which AI initiatives are integrated with and support the institution’s overarching strategic goals and mission.
2. Institutional Governance: The strength and effectiveness of governance structures in enabling AI adoption and oversight, with particular importance placed on where responsibility for AI governance is situated.
3. Stakeholder Engagement: The level of involvement and collaboration among faculty, students, and administrators in AI initiatives.
4. Operational Readiness: The institution’s capability to implement AI initiatives, including infrastructure, training, and stakeholder engagement.
5. AI Literacy and Ethical Use: The extent to which AI literacy and ethical considerations are integrated into policies, programs, and practices.
6. Accessibility and Inclusion: The extent to which AI initiatives ensure access to technology for all stakeholders, addressing affordability, infrastructure, and the needs of students with disabilities.
7. Faculty and Administrative Professional Development: The institution’s efforts to equip faculty and administrators with the skills and knowledge needed to effectively integrate AI.
8. Teaching, Learning, and Assessment Strategies: The institution’s ability to thoughtfully integrate AI into pedagogy, curriculum, and assessment, complementing human expertise.
9. Curriculum Development and Workforce Alignment: The institution’s ability to integrate AI into curricula to equip students with skills for the future workforce and align programs with emerging industry needs.
10. Research and Innovation Leadership: The institution’s ability to adopt AI-driven methods, tools, and ethical practices that enhance research processes, foster innovation, and ensure meaningful impact through effective knowledge transfer and collaboration.
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