AI-Powered Predictive Governance for Quality Assurance, Accreditation, and Academic Prestige in Higher Education

Authors

By 
Harish Alwar S
Harish Alwar S, Dr. G. U. Pope College of Engineering, India
Orcid https://orcid.org/0009-0002-0554-3760

Harish Alwar S is pursuing a Bachelor of Engineering in Computer Science and Engineering at Dr. G. U. Pope College of Engineering, Tamil Nadu, India. His research interests include artificial intelligence, higher education, digital transformation, governance, quality assurance, digital twins, and intelligent systems. He has contributed to international scholarly book chapters on AI governance, educational innovation, predictive analytics, autonomous systems, and emerging technologies. His research focuses on leveraging AI and data-driven approaches to enhance institutional effectiveness, academic quality, and evidence-based decision-making. He is committed to interdisciplinary research that bridges technological innovation with practical applications in higher education and sustainable digital transformation.

Ganesan T
Ganesan T, Dr. G. U. Pope College of Engineering, India
Orcid https://orcid.org/0009-0006-9941-1935

I am Ganesan T, pursuing my Bachelor of Engineering in Computer Science and Engineering at Dr. G. U. Pope College of Engineering, Tamil Nadu, India. My areas of interest include Artificial Intelligence, Machine Learning, and Human-AI Collaboration. I am passionate about learning, research, and exploring innovative ideas in the field of computer science.

STAR SCHOLARS PRESS

Published

Publication date : August 6, 2026

Synopsis

This chapter proposes AI-powered predictive governance as a decision-support approach for quality assurance, accreditation, and academic prestige in higher education. It argues that predictive analytics can help institutions monitor quality indicators, assess accreditation readiness, model ranking-related scenarios, and improve strategic foresight. At the same time, the chapter warns against metric fixation, algorithmic bias, and performative compliance. It emphasizes human-in-the-loop governance, ethical oversight, institutional mission, and academic judgment as essential safeguards.


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