Generative Artificial Intelligence and Transversal Competencies in Higher Education: A Systematic Review

This research aimed to analyze the importance of artificial intelligence and sustainability in higher education according to the literature in the field and to present the relationships of this context with the United Nations Sustainable Development Goals (SDGs). The adopted research strategies included bibliometric analysis using VOSviewer software and literature review, considering the Web of Science scientific database. The bibliometric analysis resulted in the clustering of four groups. The blue cluster highlighted the emergence of interest in studies on AI and sustainability in higher education following the Covid-19 pandemic. The green cluster emphasized the importance of more efficient teaching methods adapted to the demands of higher education, as well as the need to empower teachers to use artificial intelligence in developing students' skills and competencies, emphasizing sustainability. The yellow cluster indicated the presence of artificial intelligence in higher education based on the triad of sustainable education and innovation, aiming to prepare students for future challenges. The red cluster emphasized the impact of artificial intelligence in higher education, focusing on student learning, efficiency, and sustainable performance. Finally, the literature analysis identified the main AI technologies in higher education and their relationship with the United Nations SDGs. The reflections presented here can contribute to expanding discussions on the relationship between artificial intelligence and sustainability in higher education. From a practical standpoint, it can serve as a foundation for university managers aiming to promote the integration of AI into their teaching processes, considering the context of sustainability.

Artificial intelligence (AI) is scaling rapidly in higher education globally. Considering the increasing significance of artificial intelligence in higher education (AIHEd) and the absence of a comprehensive review on it, this paper delves into the evolving landscape of artificial intelligence in higher education (AIHEd), its academic integrity and ethical concerns. The study has applied qualitative approach by using literature review as a research design and method to facilitate the aim of the study.The analysis of the paper reveals that AI has the potential to make a significant contribution to enhancing teaching and learning experiences, improving productivity and efficiency, as well as fostering inclusivity and accessibility. On the contrary, the increasing utilization of AI in higher education (AIHEd) raises the concerns about academic integrity and ethical issues, as it has the potential to lead to plagiarism, impede critical thinking, suppress creativity, and erode originality in teaching, research, and scholarship. Hence, upholding the integrity of scientific research requires a rigorous commitment to ethical and academic principles, placing human intelligence and critical thinking at the forefront of the research process. The advancement of artificial intelligence in higher education not only brings significant advantages, but also poses challenges to the fundamental principles, methodologies, standards, ethical considerations and academic integrity in both teaching and research. As a result, the primary focus should be on embracing the opportunities and benefits that arise from this advancement and effectively addressing any potential risks and challenges.

The integration of artificial intelligence (AI) in higher education represents a transformative shift in the way teaching and learning are approached, offering unprecedented opportunities to enhance educational outcomes. One significant issue is the potential for bias in AI algorithms, which can perpetuate existing inequalities if not carefully managed. The objective of this study is to explore and evaluate the integration of AI in higher education to enhance teaching and learning processes. The study aims to identify the most effective AI tools and strategies for improving educational outcomes, assess their impact on student engagement and achievement, and provide actionable recommendations for educators and institutions. To effectively assess the integration of AI in higher education, a multifaceted data collection approach is essential. To ensure the successful integration of AI tools in higher education, a structured implementation plan is crucial. Enhancing teaching and learning involves a comprehensive approach that includes meticulous data collection, rigorous data analysis, strategic implementation and continuous improvement. The implementation phase requires thoughtful planning and execution, with a focus on refining AI systems based on feedback and performance metrics to ensure they effectively support educational goals. The findings show that AI integration in education has improved average grades to 88%, increased retention rates to 85%, and achieved 92% in content customisation and implementation using Python software. The future scope for integrating AI in higher education includes developing advanced AI tools that offer personalized and adaptive learning experiences, enhancing predictive analytics for student performance and retention, and fostering innovative pedagogical approaches through AI‐driven insights.

The object of the study is the status, segment analysis, dynamics and prospects of the global markets for higher education and artificial intelligence in higher education. The analysis and systematization of literature data allowed to summarize the results of research in the field of marketing research of higher education markets and artificial intelligence in higher education. To conduct a marketing analysis, the method of literature search and the method of analysis were applied. The main trends, volumes, rates and factors of growth of the higher education and artificial intelligence markets in the field of higher education, as well as some limitations of their development are presented. The analysis of the higher education market is carried out by the following segments: geographical regions, mode of study, educational levels, sources of income, educational institutions, and the market of artificial intelligence in education – market components, deployment mode, technologies, applications, geographical regions. The potential demand and volume of higher education and artificial intelligence markets in the field of higher education in different countries of the world are determined, the dynamics and competition in the world markets are tracked. The state of the art and prospects for further research in the field of higher education and artificial intelligence in education are summarized. The following scientific methods were used: the method of searching for literature data on the topic under study; the method of analyzing literary sources; comparative analysis of different methodological approaches; content analysis of documents; the method of systematization and classification in conducting research on the achievements of modern science and technology in the field of higher education and the use of artificial intelligence in higher education. The systematization of literature data allowed to present the problems of higher education and the use of artificial intelligence in higher education in the form of tables and diagrams, which gives a certain advantage for understanding and using the material.

The introduction and implementation of Artificial Intelligence (AI) in higher education has brought out new opportunities and obstacles. The utilization of AI will result in a significant transformation of the governance structure within global higher educational institutions. The potential use of AI involves exploring the educational implications of how teachers may enhance their teaching methods, how students can improve their learning experience, and how institutions of higher education can make more accurate and timely judgments. This is significant because the workload has significantly increased as a result of the widespread expansion of higher education. Given the circumstances, AI assistance is crucial. The implementation of artificial intelligence in higher education is a significant matter in this context. The objective of this study is to investigate the feasibility of individuals adopting it. To do this, we have formulated hypotheses and a conceptual framework, which we then validated through a survey by obtaining feedback from a total of 240 respondents. Research has discovered that the model can assist authorities in promoting the implementation of artificial intelligence in higher education. The outcome of this study will help practitioners understand the insights of people’s intentions and psychology in adopting AI in educational sectors.

The inclusion of Generative Artificial Intelligence (GAI) in higher education is revolutionizing teaching, learning, and research processes, presenting new opportunities and challenges to institutions worldwide. This paper explores the multidimensional inclusion of GAI in transforming higher education, with an emphasis on its applications in content development, individualized learning, and academic support systems. By utilizing algorithms capable of producing creative outputs such as text, images, and simulations, GAI enables the automation of administrative processes, increasing efficiency while promoting personalized learning experiences. This paper also looks at how GAI is utilized to enhance traditional pedagogical frameworks, giving educators new tools for curriculum creation and assessment. However, in addition to its potential benefits, GAI inclusion raises important ethical, pedagogical, and technological challenges, such as data privacy, academic integrity, and the digital divide. This paper examines the growing significance of GAI with a review of existing literature, case studies, and expert perspectives, highlighting its potential to alter educational practices while advocating appropriate applications. The findings are intended to provide an exhaustive framework for policymakers, educators, and technology developers to guide the effective and ethical integration of GAI into higher education institutions. Finally, this paper contributes to the discussion of how GAI might improve academic experiences and prepare future generations for a fast-changing technological landscape.

Background and Aim of Study: The benefits and challenges of using artificial intelligence (AI) in higher education are discussed. This has been the subject of a great deal of discussion among the general public and in the academic periodicals. The aim of the study: to specify the benefits and challenges of using AI in academic university teaching based on a review of periodical research, and to develop a classification of directions for the use of artificial intelligence in higher education for interacting stakeholders. Material and Methods: The present study used a number of theoretical methods: analysis, synthesis, comparison, generalisation, systematisation to define the benefits and challenges of the use of AI by stakeholders; classification and modelling to develop a classification of directions for the use of AI in higher education. Results: It highlights the key benefits and challenges of using AI in academic university teaching that stakeholders face. Classification of directions of AI use in higher education is developed. The following four criteria are highlighted: content of education; forms and methods of teaching; diagnosing of learning outcomes; administering of educational services. Conclusions: AI offers exciting new prospects for its application in higher education, but there are also many concerns about its rapid development First and foremost, there are the issues of the ethical and legal implications of using AI in higher education. The results of the study are important for stakeholders involved in developing strategies for the use of AI in higher education. The need to increase digital literacy and prepare all higher education institutions for the intensive process of information technology development in the coming years is highlighted.

Purpose This study explores the challenges, opportunities and future course for the use of generative artificial intelligence (GAI) in higher education to attain the targets of the sustainable development goals (SDG4). Design/methodology/approach A phenomenological approach within the qualitative research tradition was adopted. Data were collected through semi-structured interviews with 11 purposefully selected university faculty members. A hybrid data analysis procedure was employed, combining the application of a GAI model (ChatGPT 3.5) with validation by the researchers. Findings The findings revealed several challenges and opportunities that may negatively affect higher education institution (HEIs) in attaining SDG4. The study has also identified significant opportunities and has proposed future courses to align GAI with the purposes of education and attain SDG4. Research limitations/implications Equitable access to GAI-driven education requires collaboration between governments, academia and private enterprises (Target 4.3). Research-based policies must ensure AI enhances learning without undermining critical skills (Target 4.4). Inclusive AI design can improve accessibility for diverse learners while mitigating biases (Target 4.a). Educators should be empowered to integrate AI while maintaining human-centered learning environments (Target 4.c). Finally, ethical AI guidelines are crucial for fostering global citizenship and sustainable development (Target 4.7). This study underscores the need for strategic policy frameworks to maximize AI’s potential in education. Originality/value This study provides original insights into the educational use of GAI, particularly its facilitation and impediments to HEIs’ efforts to achieve SDG4. The findings offer valuable contributions to the ongoing discourse on the integration of emerging technologies in higher education and their alignment with global development objectives.

The current study aims to reveal possible opportunities for applying artificial intelligence in higher education, and to identify the most important challenges that such application faces and the maximum benefits that can be acquired from employing artificial intelligence techniques in developing the educational process and the educational services in higher education institutions. This study followed the descriptive analytical approach in addressing the topic of applying artificial intelligence in higher education by reviewing the literature and previous studies that addressed this topic. The study concluded that it is possible to benefit from the application of artificial intelligence in higher education in the fields of teaching, learning, administration, research, and others, if the requirements of this application are dealt with effectively and the facilities that support the use of artificial intelligence techniques are provided. The study recommends confronting the challenges that weaken the effectiveness of the application of artificial intelligence in higher education. The most important challenges in this regard are: the lack of educational policies related to the application of artificial intelligence in education, the weakness of the infrastructure needed to supports the use of artificial intelligence techniques, the need to train academics and learners on how to deal with new applications, and the lack of due awareness of the importance of artificial intelligence applications and its role in developing higher education. KEY WORDS: artificial intelligence, higher education, opportunities, challenges, foreseeing the future

The rapid development of Generative Artificial Intelligence (GAI) in higher education presents abundant opportunities for its high-quality development, but also introduces ethical concerns. This paper analyses the benefits of GAI in higher education in terms of teaching, learning, and evaluation. Additionally, it explores the ethical risks and reasons associated with GAI in higher education covering aspects such as data, algorithms, academia, and teacher-student relationships. The paper concludes by proposing methods and strategies to mitigate these ethical risks.

The article analyses the theoretical foundations of using artificial intelligence (AI) in higher education. It shows that the AI system as a strategic technology provides many benefits for the lives of people and society as a whole and also symbolises a new stage not only in the history of digital technologies but also on a global scale of development of modern civilisation. The article provides an overview of the policies of European and global organisations, including the United Nations Educational, Scientific and Cultural Organisation (UNESCO), the European Union, the Organisation for Economic Cooperation and Development, the European University Association, etc. on the effective use of AI in everyday life and, in particular, in education. Based on the analysis results, the article systematises ethical principles (human-centred values, governance, transparency, accountability, sustainability, proportionality, confidentiality, safety, security, and inclusiveness) that should be applied in using AI. The SWOT analysis helped identify strengths and weaknesses, opportunities and risks of using AI in higher education. The article examines the regulatory framework for the implementation of AI in the Ukrainian educational area and identifies the peculiarities of AI application in the educational process of higher education institutions. It analyses statistical data for identifying the risks and threats of using AI in HEIs under the Open Science, obtained in 2023 by researchers of the Institute of Higher Education of NAES of Ukraine in the all-Ukrainian survey “Open Science in Higher Education Institutions of Ukraine,” more than 1.5 thousand respondents participated. The article also substantiates practical recommendations for developing and implementing AI in higher education at the national, institutional and individual levels.

This study presents a comparative analysis of lecturers’ and students’ perspectives on the use of generative Artificial Intelligence (AI) in higher education at Nkhoma University, Malawi. Drawing on semi-structured interviews with 18 students and questionnaire data from 15 lecturers, this research explores awareness, perceived benefits, and challenges surrounding AI use in teaching and learning. Findings reveal that students exhibit higher awareness and engagement with AI, primarily influenced by peer interaction and social media. They use AI to enhance understanding, save time, and support independent learning. In contrast, lecturers, particularly older ones, demonstrate limited awareness and engagement, with some expressing concerns about academic integrity and the impact of AI on learning quality. Key challenges identified by both groups include ethical risks, inadequate digital infrastructure, and cognitive overreliance. The study concludes by recommending institutional training, improved infrastructure, and clear policies to ensure the responsible integration of AI in higher education.

This study integrates bibliometric analysis and systematic review methodologies to provide a comprehensive overview of research on artificial intelligence (AI) in higher education. Drawing on 621 publications and a focused analysis of 27 highly cited empirical studies, the study addresses six research questions concerning publication trends, prolific authors, influential documents, methodological approaches, research gaps and ethical considerations. The integrated design combines macro‐level field mapping with micro‐level synthesis to reveal how AI scholarship has evolved and where critical gaps persist. The findings indicate a surge in AI‐related publications since 2021, driven by generative AI in 2023–2024. Research remains concentrated in economically advantaged regions, reflecting limited participation from the Global South. Thematically, studies cluster around AI in teaching and assessment, institutional readiness and ethical implications, while theoretical fragmentation and methodological homogeneity persist. A three‐layer framework comprising technological, pedagogical, and institutional dimensions is proposed to explain these patterns and to guide more inclusive, ethical and pedagogically grounded AI integration in higher education.

This paper seeks to address the challenges of underdevelopment bedeviling the African continent in general and Zimbabwe in particular on the integration of Artificial Intelligence (AI) in higher education. Universities in Africa have over the years produced many graduates in Science, Technology, Engineering, and Mathematics (STEM) related learning areas but continue to grapple with underdevelopment both economically and intellectually. Part of the problem has been identified as a lack of quality in the education system that is not able to produce graduates with adequate 21st-century skills for the achievement of the Sustainable Development Goals (SDGs) to fulfil the Global Agenda 2030. Achieving this is possible if Africa moves a step forward and embraces modern technologies like the integration of AI in her education system. A technologically astute graduate would be able to apply their knowledge in achieving the much-needed sustainable economic development. This article highlights how the implementation of AI in higher education can foster a turnaround in Africa’s education systems and lead to industrialisation and innovation. Pivotal aspects of AI like the Turing machine test, cloud computing, big data, and machine learning are explored in an attempt to add value to the current education discourse. This study is situated in the interpretive paradigm, the qualitative approach was employed to gather data using several methods like e-questionnaires (open-ended), document analysis, and review of journals and other academic publications. Purposive sampling of STEM educators from a renowned university in Zimbabwe was undertaken to gather information on the ground and the data was thematically analysed. The article argues that Africa has the potential to be a leader in Industrialization and commerce should the continent fully embrace AI in higher education.

Emergence of the use and application of Artificial Intelligence (AI) in higher education in India has opened new possibilities and challenges. Use of AI in will bring in effective change of governance in the entire internal architecture of Indian Institutes of higher education. The prospect of use of AI includes investigation of educational implications as to how teachers would enrich them, how students would learn, and how accurate and prompt decisions can be taken in the institutes of higher education. This is important since the workload has been multiplied due to massification of higher education. Such being the scenario, help of AI is highly essential. The question of adoption of AI in higher education is an important issue in this perspective. The purpose of this study is to explore how the stakeholders would be able to adopt it. For this, we have taken help of many adoption theories and models including ‘Unified Theory of Acceptance and Use of Technology’ (UTAUT) model. We have developed hypotheses and a conceptual model and got it validated through survey with the help of feedbacks from useable 329 respondents. It has been found that the model can help the authorities to facilitate adoption of AI in higher education.