https://ir.zou.ac.zw/files/original/8ba475350178bb601c0f930fedb011f4.pdf 030d6cd484368a560ff90c0284852926 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Staff Publications Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource THE IMPACT OF AI ON PRIVACY AND SECURITY OF DATA IN UNIVERSITIES IN ZIMBABWE: A LITERATURE REVIEW Creator An entity primarily responsible for making the resource REASON GOBVU NEVER KATSAMUDANGA GODFREY TSVUURA Description An account of the resource In this empirical paper we discussed the impact of AI on data privacy and security in universities in Zimbabwe. The integration of how artificial intelligence (AI) in universities has transformed various aspects of educational systems offering enhanced efficiencies and personalised learning experiences were discussed. This technological advancement raises significant concerns regarding data privacy and security. As universities increasingly rely on AI systems that process vast amounts of sensitive information, the risk of data breaches and unauthorised access escalates. With a focus on Zimbabwe, this research offers a systematicliterature analysis of the effects of AI on data security and privacy in higher education. The study explores topics such as application of AI in universities, data privacy and security concerns, ethical and legal gaps in the application of AI and prospects for AI adoption in a responsible manner, drawing on both worldwide and regional studies. The paper is couched in Information Security Theory which evolved in the 1970s–1980s within the field of computer security as government, military and corporate institutions began formulating formal information assurance standards (Bishop, 2003). Information Security Theory model became widely recognised through the U.S Department of Defense publication and the early academic security literature. The findings suggest that AI increases efficiency and personalisation in universities, it also puts universities at risk for algorithmic bias, data breaches and poor information governance. In Zimbabwean universities, these risks are worse due to inadequate infrastructure, poor implementation of data privacy laws and regulations and insufficient knowledge. The study ends by suggesting that strong legislative policies, cybersecurity frameworks and effective digital literacy programmes should be implemented to ensure responsible AI use. Publisher An entity responsible for making the resource available The Zimbabwe Open University Journal of Applied Social Sciences Date A point or period of time associated with an event in the lifecycle of the resource 2026 Artificial Intelligence cybersecurit data security privacy universities Zimbabwe