Aug 2026· Journal of AI Range· Vol 3, pp. 55-89· 0 citations· 109 references
TL;DR
The results indicate that universities could benefit from the adoption of AI tools, data infrastructure, digital leadership, employee training, and automation processes to streamline their services, enhance data quality, decision-making, and administrative responsiveness.
Abstract
Purpose: The research in this study addresses the role of the adoption of artificial intelligence, the adoption of cloud computing, the institution's digital leadership and readiness, as well as the automation of processes in academic administration in order to understand their effects on academic administrative performance in HEIs in the context of digital transformation.
Design/Methodology: The research design used in this study is quantitative cross sectional which is a type of research design. A sample of 505 respondents with respective professions of Academic Administrators, Administrative Officers, IT staff, Quality Assurance Staff, Department Coordinators, and University Managers was obtained from institutions for Higher Education (IHEs). Partial Least Squares Structural Equation Modeling (PLS-SEM) has beenused to analyze the data.
Findings: All the results indicated a positive relationship between AI adoption, cloud computing adoption, digital leadership and institutional readiness, and academic administrative performance, and admin process automation.Results: The results showed that there is a positive relation between the artificial intelligence adoption, cloud computing adoption, digital leadership and institutional readiness, and academic administrative performance and between admin process automation and academic administrative performance. Through the results, the study also revealed that the adoption of AI, cloud, and digital leadership and institutional readiness have a significant impact on administrative process automation. Moreover, administrative process automation includes complementary partial mediation in the relations between the use of artificial intelligence, cloud computing, academic leadership and institutional preparedness, on the one hand, and academic administrative performance on the other.
Implications: The study yields a theoretical basis for the integration of technological, organizational and process-oriented approaches in the digital transformation outcomes in the higher education field. From a practical standpoint, the results indicate that universities could benefit from the adoption of AI tools, data infrastructure, digital leadership, employee training, and automation processes to streamline their services, enhance data quality, decision-making, and administrative responsiveness.
Limitations and Future Research: This study was conducted with a cross-sectional design and survey-based data.Drawbacks: This study has some disadvantages due to its cross sectional design and use of survey data. Future studies should be longitudinal or mixed-method and involve exploring other factors, including anti-change and institutional culture, cybersecurity readiness, and digital literacy.
The high adoption of digital technologies has greatly influenced the higher education environment and the integration and smart systems are essential in improving the institutional performances. One of them, the use of AI integrated ERP systems has become an essential instrument that enhances the efficiency of administration, the efficiency of making decisions based on data, and overall institutional success. The current research will focus on assessing the effectiveness of AI-based ERP systems in boosting institutional efficiency and decision-making processes in institutions of higher learning. Research methodology is empirical in which it gathers primary data comprising of academic administrators, faculty members and IT personnel related to institutions of higher education. Perceptions related to such critical dimensions as AI capability, system integration, data analytics functionality, and user adoption were captured with the help of structured questionnaires. The analysis used statistical methods, i.e., descriptive analysis and inferential methods, to investigate the association between the AI-supported ERP functionality and institutional outcomes. The results of the findings suggest that AI-based ERP systems can play a major role in enhancing decision-making with real-time access to data, predictive analytics, and administrative process automation. Moreover, the findings also emphasise the positive effect on the institutional efficiency regarding optimization of resources, speed of work, and precision of information management. The obstacles to user preparedness, data security, and system flexibility are also found in the study. The analysis is informative to policy makers, institutional leaders and technology suppliers in developing and deploying effective AI used ERP solutions in institutions of higher education. The study will add to the overall amount of research on the topic of digital transformation by providing empirical data regarding the strategic importance of AI-integrated ERP systems in improving institutional performance.
Krupa Tn, N. Dhanraj· International Journal of Eco...· 0 citations
Academic Information System (AIS) serves as a strategic digital infrastructure that supports educational service management in the digital transformation era. This study aims to analyze the role of AIS in improving educational service quality, enhancing academic administration efficiency, and increasing stakeholder satisfaction in higher education institutions. The study employed a descriptive quantitative research method using a survey approach involving 185 respondents consisting of students, lecturers, and administrative staff. Data were collected through a structured questionnaire using a 5-point Likert scale. Data analysis was conducted using descriptive statistics and Pearson correlation analysis. The results indicate that AIS implementation contributes positively to academic service efficiency, with an average user satisfaction score of 4.05 out of 5. Furthermore, a significant relationship was found between AIS feature availability and educational service quality (r = 0.742, p < 0.01). The data security dimension received the highest score (mean = 4.23), while the module integration dimension required further improvement (mean = 3.87). This study recommends continuous enhancement of system interoperability, user interface design, and human resource training to optimize AIS utilization in supporting effective educational service management.
Rafly Verdyansyah Pratama, Syariyan Nor, Joy Nashar· Devotion : Journal of Resear...· 0 citations
The study concludes that strengthening administrators’ AI competencies through continuous professional development, AI training, governance policies, and institutional capacity-building initiatives can enhance responsible AI adoption and administrative effectiveness.
Precious Kyle Cardenas, Susan Cortez, Mark Anthony De Ocampo et al.· International Journal of Sus...· 0 citations
Artificial intelligence (AI) is accelerating the digital transformation of higher education and is changing the competencies expected of Business Administration graduates. This conceptual article develops the Artificial Intelligence-Based Business Administration Learning (AI-BAL) Framework to explain how AI can be integrated into Business Administration curricula without reducing education to technology adoption. The study uses a concept-driven integrative review and theory-synthesis approach. Literature on digital transformation, artificial intelligence in education, AI literacy, management education, human-AI augmentation, and responsible AI was examined and organized through iterative concept identification, categorization, relational mapping, and framework construction. The resulting framework connects four core layers: AI technologies, digital pedagogical transformation, Business Administration competencies, and graduate outcomes. These layers are shaped by external drivers, enabled by institutional leadership, faculty capability, infrastructure, policy, and industry collaboration, and governed by cross-cutting principles of human agency, transparency, fairness, privacy, accountability, inclusion, and academic integrity. The framework positions pedagogy as the mechanism that converts technological affordances into disciplinary competence and proposes a continuous evaluation loop for curriculum improvement. Six propositions specify testable relationships among AI adoption, pedagogy, competency development, institutional readiness, and graduate outcomes. The article contributes a discipline-specific and empirically testable model for curriculum redesign, faculty development, governance, and future research in Business Administration education.
Eka Annisa Zulqaidah, Kadaruddin Kadaruddin· International Journal of Bus...· 0 citations
Digital transformation in higher education sharpens demand for the systemic design of university information and educational environments (IEEs). These environments must support personalized learning. They also sustain digital competencies and academic sustainability under hybrid-format conditions, where the quality of educational outcomes depends on how consistently the institutional digital architecture is arranged. The study centers on the development of a conceptual and methodological model of an IEE for a modern university. Its impact on the quality of educational outcomes is assessed through systemic-structural analysis and pedagogical modeling. The empirical base adds a survey of 1,240 students and 86 faculty members at five Russian universities, a case study of digital platforms, plus correlation and factor analysis. Four complementary components of the IEE are identified: technological, content- methodological, communication-network, and organizational-managerial. It has been established that the balance of components and the level of digital maturity of the teaching staff are significant predictors of students' academic performance and professional readiness. A diagnostic toolkit and optimization matrix for the information and educational system (IES) have been developed, enabling the transition from fragmented digitalization to the architecture of a holistic educational ecosystem. The research results can be used to formulate digital transformation strategies for universities, moderate accreditation procedures, and develop faculty development programs.
A. S. Yusupova, Zareta Shaayevna Abubakarova· ACCOUNTING AND CONTROL· 0 citations
This research aimed to measure the impact of digital leadership on improving the quality of decision-making using artificial intelligence (AI) technologies in private universities in Baghdad, with Al-Farabi University serving as a case study. The research stemmed from the crucial role of digital leadership in guiding technological transformation within academic institutions, particularly given the increasing reliance on data, smart systems, and AI applications to support administrative and academic decisions. The study employed a descriptive-analytical approach, utilizing a questionnaire as the primary data collection tool. The questionnaire was administered to a sample of 112 employees at Al-Farabi University. The independent variable, digital leadership, was measured through two dimensions: digital vision and digital empowerment. The dependent variable was measured through the quality of decision-making using AI technologies. Reliability results showed high Cronbach's alpha coefficients for all dimensions, with the overall reliability coefficient for the questionnaire reaching 0.95, indicating the instrument's consistency and validity for analysis. Furthermore, multiple linear regression analysis revealed a significant impact of digital vision and digital empowerment on the quality of decision-making, with a coefficient of determination of 0.66. This suggests that the dimensions of digital leadership explain 66% of the variance in decision-making quality. The research concluded that digital leadership represents a crucial administrative approach to improving university decision-making when linked to a clear vision, effective digital empowerment, and a technological infrastructure capable of supporting the use of artificial intelligence.
M. Abdulhadi· International Journal of Fin...· 0 citations
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