Artificial Intelligence and Digital Capabilities for Service Excellence in Higher Education: a Critical Review of Emerging Trends and Research Gaps
Year: 2025
Type: article
Abstract: Increasing awareness is that digital literacy and artificial intelligence (AI) are capable of transforming higher education to embrace academic excellence, administrative effectiveness, and fair learning. However, unequal and theoretically underdeveloped usage of these technologies in higher education still persists. The systematic review employs 48 peer-reviewed papers from 2017 to 2025 according to the PRISMA protocol. In synthesizing conceptual and empirical literature on the potential of AI to enhance university service delivery, thematic matrix approach was employed. The research showed that artificial intelligence has a relevant role to play in three important aspects of higher education. First, enhances the process of learning through predictive testing, adaptive learning, and smart teaching and thus enhancing student performance. Second, drives administrative efficiency by automating tasks, enhancing data-driven decision-making, and improving institutional planning. Thirdly, enhances equity and inclusivity by ensuring that marginalized communities and disability students get education services. In light of this benefit, the research discovered pervasive gaps that will cap the actual potential of AI. Such gaps include the absence of models in complete implementation, the absence of focus on moral and legal matters, and the absence of positive action to prepare teachers and support institutions to implement these paradigms. For maximum utilization of AI in higher learning, universities should adopt transparent ethical standards, invest funds in enhancing students' and instructors' online proficiency, and encourage interdisciplinarity. These are key steps towards ensuring that the application of AI is in accordance with the educational mission and institutional values of the academy.
Source: PRSM
Authors: AL HOSNI, SAMI SALIM, CHAKOR, ABDELLATIF, AL-ANSI3, ABDULLAH M.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W6927726140
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