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This study presents a systematic literature review analysing the impact of artificial intelligence (AI) on higher education, focusing on its methods, results, and implications. By synthesising a diverse range of academic papers, the review explores how AI technologies influence educational standards and practices in higher education institutions. Findings reveal that AI has the potential to enhance the quality of higher education by diversifying teaching responsibilities, customising learning experiences, and employing intelligent, adaptive teaching strategies. These capabilities position AI as a transformative tool for improving educational delivery and outcomes. However, the study also highlights significant challenges associated with integrating AI into higher education. These challenges include delineating the appropriate scope of AI use, addressing inequalities in access to digital resources, and ensuring adequate training and support for educators and students. The review underscores the importance of understanding these complexities to guide the development of effective strategies and policies that optimise AI's potential while mitigating its limitations. The review offers critical insights into the dual role of AI in higher education, where it can either advance or hinder educational standards depending on how it is implemented. By examining the advantages, limitations, and broader consequences of AI-powered instructional tools, this study provides a comprehensive perspective on the intricate relationship between AI and educational quality. The findings aim to inform educators, policymakers, and stakeholders about the opportunities and challenges of adopting AI in higher education, contributing to the development of inclusive, innovative, and sustainable educational practices.

This study explores Artificial Intelligence’s potential in promoting social inclusion in South African tertiary institutions. Despite advancements in expanding access to higher education, historical disparities continue to exclude marginalised groups from accessing equal opportunities in education and human capital development. Artificial Intelligence (AI) offers a promising avenue to bridge this gap by enhancing accessibility, promoting personalised learning, and streamlining administrative processes. The study adopts a desktop literature review to explore how AI-powered tools can leverage intelligent assistive technologies, personalised learning experiences and automated administrative tasks that reduce bureaucratic barriers to enhance physically challenged students’ accessibility and address their diverse learning styles and needs. Despite the potential benefits of AI tools, challenges such as the digital divide, infrastructure constraints, AI bias, cultural sensitivity, and institutional capacity persist to hinder massive adoption. The study recommends infrastructure development, digital literacy programs, culturally sensitive AI design, and capacity-building initiatives for educators to fully harness AI's potential for social inclusion in higher education institutions. The study contributes new knowledge to the ongoing discourse on AI-driven social inclusion in higher education. It emphasises opportunities and challenges prevalent in South Africa. Hence, the study demonstrates how leveraging AI can foster a more inclusive and equitable learning environment

Artificial Intelligence (AI) integration has become increasingly prevalent in various industries, transforming business processes and creating new opportunities. As AI continues to shape the future of work, organisations such as Higher Education Institutions (HEIs) must scrutinize their readiness to develop a workforce competent in AI. AI competencies are fundamental to successfully enacting and integrating these technologies. As a result, several organisations have invested in workforce readiness, albeit these efforts are affected by several actors and determinants. Consequently, organisations must examine the workforce readiness for AI integration as a technology of the future. This paper aims to explore the integration of AI in organisations such as HEIs to ascertain workforce readiness. Addressing three pivotal research questions, it delves into the extent to which the workforce in HEIs is developed and competent in AI, the contributing factors shaping the integration of AI into HEIs’ workforce, and the overall readiness of HEIs in fostering workforce development within the realm of AI. Employing a systematic content analysis review, the study provides pragmatic findings, serving as a reference point to elevate workforce readiness and pinpoint critical determinants. The study identified factors contributing to AI competency development that serve as valuable insights for other institutions aiming to design and implement effective workforce development programs in AI. Also, the findings provide significant implications for institutions seeking to enhance their workforce's competency in AI.   Keywords: Artificial Intelligence, Higher Education Institutions, HEIs, Workforce, Readiness.

Artificial intelligence has become an integral part of higher education, significantly transforming the landscape of higher education. This study aims to identify, analyse and visualise peer-reviewed academic research output on artificial intelligence (AI) and graduate attributes in higher education. Data was gathered from the Scopus database over a decade (2014-2024), with search terms related to artificial intelligence, graduate attributes, and higher education. Following the PRISMA method guidelines, 106 articles were deemed necessary for review. Bibliometric methods, content and thematic analysis were used to identify main themes, and VoSviewer software was used to analyse the data. The findings revealed research productivity, citation overview, the main subjects, the territory of the leading researchers, thematic choices and future research opportunities and directions. Themes such as the impacts of AI on graduate attributes emerged, which may assist policymakers, educational institutions, teachers and students in their strategies and choices for adopting and using AI. The study recognised research trends, provided insights into the current state of AI and higher education research, and identified potential gaps in the literature on the research landscape of AI, graduate attributes, and higher education. The study can guide future researchers on emerging thematic opportunities.

Artificial Intelligence (AI) is transforming higher education, offering both pedagogical advantages and potential academic risks for teaching and learning. This systematic review consolidates existing research to examine whether AI enhances or hinders pedagogical practices in universities. Results show that AI boosts efficiency, supports personalization, and promotes inclusivity through adaptive learning systems, intelligent tutoring platforms, and automated assessment tools. The findings, however, also indicate risks such as academic integrity issues, algorithmic bias, unequal access, and the potential deskilling of educators. Furthermore, policy gaps exacerbate these risks, subjecting institutions to ethical dilemmas and inconsistent practices. The review concludes that responsible integration, supported by strong governance frameworks, drives the impact of AI in academia. Recommendations for policymakers include introducing clear institutional policies for the use of AI in higher education, promoting equitable access to digital infrastructure, and mandating transparency and accountability to ensure trust and fairness in high-stakes decision-making. For higher education institutions, establishing comprehensive guidelines for AI use, investing in faculty training, and redesigning assessments can help ensure inclusivity, preserving creativity, and emphasizing originality and problem-solving skills less easily replicated by AI.

Sophisticated AI applications like ChatGPT and Grammarly offer distinct advantages for enhancing writing proficiency. They assist users in conceptualising ideas, organising material, and refining writing style, whereas Grammarly focuses on improving grammar, punctuation, and clarity with context-aware recommendations. This is particularly relevant for students who are non-native English speakers, as it supports them and helps bridge educational disparities. While these instruments markedly enhance scholarly writing abilities, their efficacy in tertiary education remains a subject of debate. Recent occurrences of academic dishonesty associated with the improper use of generative AI technologies have negatively impacted higher education. This study assesses the impact of artificial intelligence on enhancing academic writing abilities in students who are not native English speakers. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, this study consolidates evidence from scholarly literature, policy reports, and institutional case analyses. Keywords, synonyms, and subject headings were employed to query three electronic databases from 2021 to 2025. The electronic repositories included Scopus, Emerald Insight, Google Scholar, and ProQuest. The evaluation of the publications was conducted through titles and abstracts, followed by an assessment of the full-text papers against the qualifying criteria. The results were derived and amalgamated into a narrative synthesis from selected publications. The results underscored AI's ability to customise and improve the educational experience for learners.

This systematic review examines artificial intelligence (AI)-powered digital transformation in mathematics education as a strategic business ecosystem issue rather than only a classroom technology concern. The objective is to synthesise how AI-supported pedagogies create educational value, what ecosystem risks accompany adoption, and which organisational capabilities and governance conditions enable responsible implementation. Guided by PRISMA 2020 principles, peer-reviewed empirical and conceptual studies published between 2018 and 2025 were identified from Scopus, Web of Science, ERIC, Education Source and Google Scholar. A total of 3,241 records were initially retrieved; after duplicate removal, screening and full-text eligibility assessment, 203 studies were included for structured extraction, quality appraisal and thematic synthesis. The evidence was analysed through a business ecosystem lens focusing on value co-creation, stakeholder interdependence, digital governance, teacher capability, infrastructure readiness and equity. The findings show that AI tools can strengthen adaptive practice, formative feedback, diagnostic analytics, multimodal representation and teacher decision-making when they are embedded in coherent institutional strategies. However, strategic value is weakened by digital inequality, data privacy risks, algorithmic opacity, cognitive offloading, platform dependence, weak curriculum alignment and insufficient teacher capability. The study contributes an ecosystem strategy framework that positions AI as a pedagogical and organisational mediator within a network of learners, teachers, institutions, technology providers, policy bodies, infrastructure actors and communities. It concludes that AI adoption in mathematics education should be strategy-led, ethically governed and capability-driven. Sustainable value creation requires inclusive infrastructure, teacher professional development, data governance, assessment redesign, transparent procurement and partnerships that protect educational equity while enabling innovation in resource-constrained and digitally uneven contexts.

Artificial Intelligence (AI) is transforming higher education, offering both pedagogical advantages and potential academic risks for teaching and learning. This systematic review consolidates existing research to examine whether AI enhances or hinders pedagogical practices in universities. Results show that AI boosts efficiency, supports personalization, and promotes inclusivity through adaptive learning systems, intelligent tutoring platforms, and automated assessment tools. The findings, however, also indicate risks such as academic integrity issues, algorithmic bias, unequal access, and the potential deskilling of educators. Furthermore, policy gaps exacerbate these risks, subjecting institutions to ethical dilemmas and inconsistent practices. The review concludes that responsible integration, supported by strong governance frameworks, drives the impact of AI in academia. Recommendations for policymakers include introducing clear institutional policies for the use of AI in higher education, promoting equitable access to digital infrastructure, and mandating transparency and accountability to ensure trust and fairness in high-stakes decision-making. For higher education institutions, establishing comprehensive guidelines for AI use, investing in faculty training, and redesigning assessments can help ensure inclusivity, preserving creativity, and emphasizing originality and problem-solving skills less easily replicated by AI.

The use of artificial intelligence (AI) in higher education entrepreneurship education (EE) is an important advancement that integrates innovative technology with teaching methods.  Even so, the research output in this new field is still disjointed and unclear. This study delineates key trends, prominent authors, thematic evolution, and collaboration patterns using a bibliometric analysis of 50 publications from the Web of Science database (2016-2025). Drawing on the output from Biblioshiny software, the results indicate a rapid growth in research output after 2022. This is largely attributed to generative AI developments.  Key areas of research have, also, shifted over time from a general focus on pedagogy to groupings that focus on technology, such as using AI in education, focusing on student consequences, and entrepreneurial intentions. The results show a leading contribution to research output from China. International partnerships, on the other hand, are decentralised. Also, the overall network of co-authors is still fragmented. The study’s conclusion indicates that the field is transforming into a synthesis of technological and human-centric frameworks showing an interdisciplinary convergence of education, psychology, and computer science. It also points out more research avenues, such as the need for more qualitative studies on implementation and a closer look at the ethical side of AI in education.

The growing use of AI in higher education has heightened interest in genuine e-assessment to improve assessment efficacy, inclusivity, and academic integrity. Nonetheless, the implementation of AI-enhanced assessment techniques in South African higher education is inconsistent, influenced by structural disparities, ethical dilemmas, and differing degrees of institutional preparedness. This study offers a qualitative systematic literature analysis that investigates the implementation issues and pedagogical ramifications of AI-enhanced genuine e-assessment at South African Higher Education Institutions (SAHEIs). The evaluation, structured using a PICo-informed framework and according to PRISMA principles, synthesised evidence from 49 peer-reviewed publications published from 2020 to 2024. A narrative theme synthesis was utilised to examine persistent patterns concerning implementation obstacles, ethical considerations, assessment change, inclusion, and governance. AI-driven assessment technologies have significant advantages, such as higher grading consistency, scalability, tailored feedback, and increased student involvement. Nonetheless, infrastructural constraints, ongoing digital disparities, inadequate faculty readiness, and the lack of cohesive institutional policies hinder these advantages. Ethical concerns, especially algorithmic bias, data privacy, and academic integrity, exacerbate the implementation of AI in varied and resource-limited settings. This analysis finds hybrid evaluation models that integrate AI automation with human judgement as the most pedagogically sound and ethically responsible method. The study indicates that AI-enhanced authentic e-assessment possesses transformative potential for SAHE, contingent upon context-sensitive policies, ongoing professional development, equitable infrastructure investment, and strong ethical governance frameworks.