Jul 2026· International Journal of Sustainability and Advanced Integrated Research· 0 citations· 38 references
TL;DR
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.
Abstract
The rapid advancement of Artificial Intelligence (AI) has transformed higher education administration, requiring institutions to strengthen leadership capacity, technological readiness, and responsible governance. This study aimed to examine the administrative practices of higher education institutions in the age of Artificial Intelligence at the University of Perpetual Help System JONELTA (UPHS JONELTA). It was anchored on Transformational Leadership Theory and the Technology Acceptance Model (TAM) to understand leadership practices, technology acceptance, and AI integration. The study employed a descriptive-quantitative research design involving 89 administrators from UPHS JONELTA campuses. Data were collected using a structured survey questionnaire and analyzed through descriptive statistics, independent samples t-test, one-way ANOVA, simple linear regression, and multiple regression analysis. Findings revealed that administrators demonstrated a high level of AI readiness and usage, with strategic leadership obtaining the highest rating. AI readiness and usage were also perceived to have a high impact on administrative practices, particularly in decision-making efficiency, operational efficiency, communication and collaboration, and strategic planning. Results further showed that AI readiness and usage significantly predicted administrative practices, with strategic leadership and data-driven decision-making identified as significant predictors. 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. The study supports SDG 4 (Quality Education) by contributing to improved educational leadership and institutional capacity, and SDG 16 (Peace, Justice, and Strong Institutions) through its emphasis on responsible governance, ethical AI integration, and accountable decision-making. Its sustainability impact lies in promoting institutional and digital sustainability by strengthening leadership, policies, and practices needed for long-term AI-enabled transformation in higher education.
The study investigated the awareness, use and institutional readiness for adopting Artificial
Intelligence (AI) in some selected polytechnics in Adamawa and Taraba States, Nigeria. The study
is designed to evaluate the preparedness of stakeholders in relation to AI implementation, and
assess the extent of use of Artificial intelligence practices in Teaching-Learning and administrative
processes. This study employed a descriptive survey design, using a quantitative approach. Data
were collected from a cohort of academic staff, administrative staff, ICT personnel and students
via a structured questionnaire that was validated in terms of content, reliability and usability by
members of the target population and then analysed using descriptive & inferential statistics. The
results show that respondents are somewhat knowledgeable about AI and view its potential to
improve educational outcomes in a favorable light. On the other hand, institutional readiness is
assessed to be low with major deficiencies in infrastructure, staff training and policy frameworks.
The research also finds that AI usage in academics and administrative areas tends to be largely
confined to niche pockets like research support. The conclusion is that there is strong awareness
and willingness among stakeholders, but the poor institutional capacity limits effective deployment
of AI. It calls for greater investment in infrastructure, capacity-building and those clear policies
be developed to guide the gradual and sustainable integration of AI into tertiary education.
Mohammed Hamidu· Research Journal of Pure Sci...· 0 citations
This empirical study examined the relationship between the use of Artificial Intelligence (AI) and perceived student learning outcomes and faculty efficiency in higher education institutions in the United Arab Emirates (UAE), informed by the UAE National Strategy of Artificial Intelligence 2031.
A quantitative, cross-sectional survey was administered to 128 students and faculty members across four selected UAE universities; correlation and multiple regression analyses were used to test the study hypotheses.
AI utilization had significant, positive relationships with perceived student learning outcomes and faculty efficiency; institutional readiness was not an independent predictor of either outcome in the regression models.
These findings indicate that greater AI use is associated with more positive perceptions of learning outcomes and faculty productivity, although the cross-sectional design does not permit causal inference. The results can inform institutional planning for AI integration in UAE higher education and future research on this topic.
Wafa Salim Aljneibi, W. Frick· Frontiers in Education· 0 citations
As artificial intelligence (AI) becomes increasingly fundamental to education systems globally, public senior secondary schools in Lagos State, Nigeria face the urgent need to assess their readiness for AI integration. This study examined the relationship between transformative educational leadership and AI readiness in selected public senior secondary schools in Lagos State. Specifically, the study investigated the relationships between administrative efficiency, resource management, and digital literacy, and institutional AI readiness indicators such as digital skills, staff capacity, and organisational preparedness. A quantitative research design was adopted, and data were collected from 50 principals in Education District V, Lagos State, using a structured questionnaire. Data were analysed using descriptive statistics and Pearson correlation analysis. Findings revealed significant positive relationships between leadership variables and AI readiness. Administrative efficiency showed the strongest correlation with AI readiness (r = .62, p < .01), followed by resource management (r = .54, p < .01). Digital literacy also showed a significant but comparatively weaker relationship with AI readiness (r = .54, p < .01), indicating its continued importance as a developmental challenge in schools. The study concludes that transformative educational leadership is a significant predictor of AI readiness in public senior secondary schools in Lagos State, Nigeria. It recommends targeted leadership training, improved policy frameworks, and increased investment in digital infrastructure to support effective and equitable AI adoption in schools.
S. Oladipo, S.O. Okewole· Lagos Education Review· 0 citations
Artificial Intelligence (AI) is increasingly integrated into higher education. However, its effectiveness in enhancing student competencies and professional readiness remains uncertain. This study examines the extent to which AI adoption contributes to the development of key competencies and professional readiness among Generation Z students at Universiti Utara Malaysia (UUM). A mixed-methods approach was employed involving 150 undergraduate students, supported by semi-structured interviews with 10 lecturers and student representatives. The study is guided by a conceptual framework linking AI adoption to critical thinking, digital literacy, ethical reasoning, and professional readiness. Findings indicate a moderate level of AI adoption, with students primarily using AI tools for productivity and assignment preparation, while engagement in creative and innovative applications remains limited. Although digital literacy shows improvement, enhancements in critical thinking and ethical awareness are less evident. Qualitative findings further reveal a tendency among students to over-reliance on generative AI outputs without critically evaluating accuracy, bias, or reliability. Lecturers also expressed concerns regarding the absence of structured AI pedagogy and clear institutional guidelines governing AI use in academic settings. In addition, only a small proportion of students demonstrated confidence in applying AI within professional contexts such as urban planning and related fields. Overall, the study concludes that AI adoption alone does not guarantee the development of meaningful competencies or professional readiness. It emphasizes the need for curriculum enhancement, clearer institutional policies, and targeted capacity-building initiatives that integrate AI literacy, ethical considerations, and discipline-specific applications to ensure responsible, critical, and effective use of AI among future graduates in complex professional environments.
Unknown authors· Journal of governance and de...· 0 citations
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.
The rapid integration of Artificial Intelligence (AI) in higher education has changed teaching and assessment practices and has introduced new risks for faculty well-being. This study, conducted in 10 public and private universities in Dhaka, Bangladesh, examines faculty burnout associated with AI adoption and academic integrity enforcement. Semi-structured interviews were conducted with 37 full-time faculty members, each with more than 5 years of teaching experience. Reflexive thematic analysis identified 5 domains of burnout: workload intensification through invisible labor, technostress driven by rapid technological change, an investigative burden that moves the faculty role from pedagogy toward surveillance, ethical strain within a policy vacuum, and disruption of professional identity. Participants described AI integration as a structural intensifier of academic labor rather than a labor-saving tool. In the absence of clear governance, faculty members absorbed the cognitive, emotional, and administrative costs of institutional transitions. The findings support the need for written institutional AI policies, formal recognition of assessment redesign labor, fair and reliable misconduct procedures, and sustained professional development so that integrity enforcement does not rest on individual instructors alone. The results carry implications for university governance, national regulatory bodies, and occupational health in academic workplaces.
Ridwan Islam Sifat, Mohaimenul Islam Jowarder, Rafiul Azim Jowarder et al.· New solutions : a journal of...· 0 citations
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