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A transformative shift is imminent as generative artificial intelligence facilitates a synthetic and highly individualised approach to information creation and transmission. Technological breakthroughs and innovations necessitate the integration of technology across all facets of life, operations, and education to improve efficiency and effectiveness. Numerous institutions worldwide have adopted Generative AI (GenAI) as a revolutionary tool in educational dialogue, encompassing teaching, learning, student participation, and research. The study sought to assess digital innovations using GenAI, video platforms, and social media within the educational sphere. A mixed-methods design was employed including 225 participants. Research indicated that AI improves personalisation and engagement, while video and social media tools promote collaboration and digital literacy. GenAI can automate administrative functions, support multidisciplinary research, and enhance dynamic and interactive learning experiences. Artificial intelligence can automate and improve several processes, facilitating support for both learners and educators, from managing routine enquiries to optimising resource allocation via predictive analytics. Video educational platforms facilitate the creation of interactive and customised content. Social media may augment initiatives, cultivate digital literacy, and promote user-generated content. The research suggests that effective integration necessitates ethical AI knowledge and institutional capability.

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.