Abstract

Higher education’s complexity and the demand for AI in decision-making necessitate exploring assessment and evaluation tasks. This systematic literature review of 10 articles from the ACM Digital Library and Scopus identifies six primary themes: developing optimized teaching strategies, transfer credit evaluation, selecting performance-based feedback, evaluating faculty applicants, identifying AI misuse, and institutional success planning. Notably, only one theme addresses AI assistance for futuristic predictions within uncertain environments. These findings provide actionable insights for practitioners, researchers, and policymakers, emphasizing the urgent need for responsible AI integration in higher education decision-making frameworks.