Governance structures that exclude faculty and support staff responsible for implementation produce policies that do not stick¶

Claim · All claims
Evidence · 1 study · qualitative r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Committees that built in genuine instructional input produced guidelines faculty trusted and used; those that did not produced policies faculty ignored or worked around. → Jacob 2026

Evidence¶

Jacob 2026¶

Jacob, S., Miceli, H., Schneider, H., & Peters Hinton, V. (2026). Institutional conditions for integrating emerging technologies in higher education. Digital Promise. https://doi.org/10.51388/20.500.12265/294

q2 · i? · qualitative · r2

Focus group finding: faculty and frontline staff were often only vaguely aware of AI committees or unrepresented in them; a contrasting example was an "AI enablement team" pairing IT experts with faculty representatives, credited with better decisions and smoother rollouts.

"Governance structures that exclude the faculty and support staff responsible for implementation produce policies that don’t stick. Committees that built in genuine instructional input produced guidelines faculty trusted and used; those that didn’t produced policies faculty ignored or worked around."

Discussion¶

Related Claims¶

• Technology implementation in higher education depends on individual initiative rather than institutional systems, with governance structures rarely including those responsible for implementation — related
• Interview respondents identify collaborative relationships, trust in evidence and its users, clarity on research types, and supportive leadership as facilitators of evidence use — related
• Knowledge alone did not ensure meaningful participation; it became influential when clearly communicated and built into programming — related
• Dispositions such as openness and shared responsibility are shaped by conditions, not fixed individual traits — related
• Female principals empowered others through shared ownership, committee involvement, and staff development — related
• Governance model shaped AIAS adoption: rapid central rollout generated momentum but curtailed reflection, while department-led adoption built ownership but fragmented strategy — a narrower finding that bears on this claim
• Students most often urge institutions to teach responsible AI use (N=41) and provide clear rules and guidelines (N=27) — related
• Government regulations and policy incentives are crucial external enablers of institutional AI adoption readiness — related
• Empowering and distributive leadership styles are associated with greater faculty engagement and willingness to adopt AI in higher education, per the reviewed studies — related