This paper presents a comprehensive and integrated paradigm for intelligent universities using artificial intelligence (AI) to transform management systems and teaching, thus complementing sustainable development objectives. Through a systematic examination of top worldwide universities’ AI applications, this study reveals key achievements, obstacles, and strategies for successfully implementing AI-driven intelligent universities. Every case study focuses on a particular AI-driven project, including the adaptive learning systems at MIT, the AI teaching assistant Jill Watson at Georgia Tech, and the AI-enabled quality control system at Cambridge University. Combining systematic review, meta-analysis, and case studies under a mixed-methods approach, the study provides a practical guide for implementing artificial intelligence to improve administrative and academic roles. Results show how artificial intelligence can solve institutional issues, automate quality assurance, and personalize learning. Recommendations advocate for gradual adoption strategies, ethical AI deployment, and capacity-building measures to enable sustainable digital transformation.

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