Embed anticipatory governance in institutional strategy via Chief AI Officers, AI task forces, faculty AI-literacy development, and student co-design mechanisms¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The review's practical recommendations translate its findings into implementable actions for university leaders, faculty, and institutions. Leaders are "encouraged to embed anticipatory governance into institutional strategies by establishing roles such as Chief AI Officers or AI task forces to align curriculum, policy, and infrastructure with emerging technological and workforce demands". Faculty should pursue professional development strengthening AI literacy and foresight methods to act as co-creators of future-ready curricula. Institutions should create student councils on AI policy or co-design workshops, and form partnerships with industries and local communities so AI policies reflect local needs and values.

Design Implications¶

Context¶

Requirements¶

• Institutional commitment to aligning curriculum, policy, and infrastructure
• Professional development structures for faculty AI literacy
• Mechanisms for student voice such as councils or co-design workshops

Constraints¶

• The review notes many institutions, especially in the Global South, lack the digital assets, infrastructure, faculty readiness, and policy frameworks these recommendations presuppose

Target Learners¶

• University leaders and administrators
• Higher education faculty
• Students

Target Learning Goals¶

• Responsible AI integration in teaching and governance
• AI literacy and pedagogical innovation
• Student agency in AI policy shaping

Affordances¶

• Anticipatory Governance Framework Higher Education Ai

Claims¶

• AI outcomes in higher education are shaped by leadership capacity, infrastructure readiness, and governance structures rather than functioning independently [+W]

Related Strategies¶

• Foster communities of practice for AI governance instead of rigid top-down policies
• Co-create contextualized AI literacy policies via multi-stakeholder task forces with phased roadmaps
• Four strategic recommendations for supporting AI literacy across settings
• Convene cross-functional generative AI task forces to guide ethical adoption decisions and procurement
• Incorporate AI literacy into educational-leadership preparation curricula
• Staged institutional implementation: audit interactions, map to teaming levels, build AI literacy, co-design, and evaluate iteratively
• Staged readiness strategy: establish policy clarity and faculty capacity-building before ambitious AI-enabled or online scale-up
• Combine bottom-up co-design with top-down executive sponsorship, cross-unit collaboration and dedicated R&D capacity to embed institutional GenAI

Examples¶

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Key Sources¶

• Sandra Baroudi. (2026). Anticipatory governance and leadership for AI implementation in higher education: A scoping review. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00616-7