Article: Artificial intelligence - driven digital transformation framework for smart universities Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.86 pp.1 - 33 Abstract: This study examines the incorporation of artificial intelligence into intelligent institutions, focusing on the lack of a cohesive closed-loop architecture that integrates multimodal data intelligence, decision analytics, and policy optimisation. The AI-orchestrated digital transformation framework (AI-ODTF) has three levels: data intelligence, decision intelligence, and governance optimisation. multimodal data, relational embeddings, and transformer-based temporal encoding are used to make a single institutional knowledge graph. Ensemble prediction and Bayesian causal inference make it possible to evaluate policies that do not happen, while reinforcement learning with multi-objective optimisation finds the best balance between quality, cost, and sustainability. The framework is confirmed utilising the xAPI-Edu-Data dataset, employing an 80:20 train-test division and five-fold cross-validation. AUC, RMSE, F1-score, and counterfactual gain are all used to measure performance. The results show big improvements, such as an AUC increase from 0.74 to 0.91, a 19.6% increase in resource efficiency, and a 17.9% increase in overall performance. Inderscience Publishers - linking academia, business and industry through research

Title: Artificial intelligence - driven digital transformation framework for smart universities

Authors: Zhiwang Ding; Chong Xu; Hongjuan Li; Chaoyang Xiao

Addresses: Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, Jiangxi, China ' Network and Information Technology Center, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, Jiangxi, China ' College of Continuing Education, Jiangxi University of Traditional Chinese Medicine, 1688 Meiling Ave., Nanchang, 330004, Jiangxi, China ' School of Acupuncture and Massage, Jiangxi University of Traditional Chinese Medicine, No. 1688 Meiling Avenue, Nanchang City, Jiangxi Province, 330004, China

Abstract: This study examines the incorporation of artificial intelligence into intelligent institutions, focusing on the lack of a cohesive closed-loop architecture that integrates multimodal data intelligence, decision analytics, and policy optimisation. The AI-orchestrated digital transformation framework (AI-ODTF) has three levels: data intelligence, decision intelligence, and governance optimisation. multimodal data, relational embeddings, and transformer-based temporal encoding are used to make a single institutional knowledge graph. Ensemble prediction and Bayesian causal inference make it possible to evaluate policies that do not happen, while reinforcement learning with multi-objective optimisation finds the best balance between quality, cost, and sustainability. The framework is confirmed utilising the xAPI-Edu-Data dataset, employing an 80:20 train-test division and five-fold cross-validation. AUC, RMSE, F1-score, and counterfactual gain are all used to measure performance. The results show big improvements, such as an AUC increase from 0.74 to 0.91, a 19.6% increase in resource efficiency, and a 17.9% increase in overall performance.

Keywords: artificial intelligence; digital transformation framework; smart universities; data intelligence layer; decision intelligence layer; governance optimisation layer.

DOI: 10.1504/IJICT.2026.155561

International Journal of Information and Communication Technology, 2026 Vol.27 No.86, pp.1 - 33

Received: 24 Feb 2026
Accepted: 21 Apr 2026
Published online: 05 Aug 2026 *

Title: Artificial intelligence - driven digital transformation framework for smart universities

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