Quality literature-based research identifies institutional barriers in AI integration in universities, suggesting pathways for improvement.
This paper examines Faculty Preparedness and Institutional Challenges in AI Capacity Building. It explores how Artificial Intelligence is transforming teaching, learning, assessment, and administrative processes in universities. Despite growing awareness of AI tools among educators, many faculty members still lack adequate digital skills, pedagogical training, and ethical understanding required for effective AI integration. The study also highlights institutional barriers such as limited infrastructure, unclear policy frameworks, insufficient professional development programs, and resistance to organizational change. Using a qualitative literature-based approach, the research emphasizes the need for a holistic strategy involving continuous faculty training, strong leadership support, ethical governance, and long-term institutional planning for sustainable AI adoption.
No takes yet. Share an insight, caveat, or question.
A. K. Hazra (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: