Please use this identifier to cite or link to this item: https://bura.brunel.ac.uk/handle/2438/34155
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dc.contributor.authorOsmani, Zejneb-
dc.contributor.authorAlthonayan, Abrahim-
dc.coverage.spatialTirana, Albania-
dc.date.accessioned2026-11-11T17:34:03Z-
dc.date.available2026-11-11T17:34:03Z-
dc.date.issued2025-10-21-
dc.identifier.citationOsmani, Z. and Althonayan, A. (2025) 'AI-Driven Digital Transformation in HE Marketing: Opportunities and Challenges in Student Recruitment', 5th International Conference, ICITTBT 2025, Tirana, Albania, 29–30 May. pp. 504–513. doi: 10.1007/978-3-032-07370-9_37.en_US
dc.identifier.isbn9783032073693-
dc.identifier.isbn9783032073709-
dc.identifier.issn1865-0929-
dc.identifier.otherhttps://doi.org/10.1007/978-3-032-07370-9_37-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/34155-
dc.description.abstractThe digital transformation in higher education (HE) marketing has accelerated rapidly after the artificial intelligence (AI) advancement, especially through the integration of generative AI technologies. Institutions are increasingly relying on these innovations to enhance outreach, personalization, and operational efficiency. Among the most promising applications is the use of AI-powered recruitment assistants, capable of providing multilingual, personalized, and real-time support to prospective students and their families. This paper explores generative AI within the student recruitment marketing strategy of university, focusing on its capacity to address long-standing recruitment challenges in the higher education sector. This paper highlights the transformative potential of AI in redefining recruitment paradigms, bridging communication gaps, and strengthening global outreach. It also underscores the necessity for ethical and strategic implementation to ensure transparency, accuracy, ethics and data security in higher education marketing. To address these issues, Canadian Institute of Technology University College (CIT) implemented an AI-driven recruitment assistant using a Large Language Model (LLM) enhanced with Retrieval-Augmented Generation (RAG). This approach enabled the development of a generative AI ChatBot, named CITBot grounded in CIT’s official documentation and web resources, including regulations, academic strategies, and admission procedures. To assess the impact and user satisfaction, a survey was conducted with 20 high school students and parents. The survey was administered through structured online questionnaires immediately following their chatbot interaction. The results indicated strong acceptance and a high level of willingness among users to adopt the new technology. Participants reported positive experiences regarding the clarity, accuracy, and helpfulness of the information provided. CITBot also proved to be a valuable tool in helping users better understand University's academic offerings and administrative procedures.en_US
dc.format.extentpp. 504–513-
dc.format.mediumPrint-Electronic-
dc.languageEnglishen_US
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofseriesCommunications in Computer and Information Science (CCIS);volume 2670-
dc.relation.ispartofseriesInternational Conference on Intelligence-Based Transformations of Technology and Business Trends-
dc.rightsRe-use licence for this version: InCopyright-
dc.rightsLicence for published version: Publisher's own licence-
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/-
dc.source5th International Conference, ICITTBT 2025-
dc.subjectAI-driven marketingen_US
dc.subjectgenerative AIen_US
dc.subjectstudent recruitmenten_US
dc.subjectrecruitment assistanten_US
dc.subjectmultilingual chatboten_US
dc.subjectlarge language model (LLM)en_US
dc.subjectdigital transformation in higher education admissionen_US
dc.titleAI-Driven Digital Transformation in HE Marketing: Opportunities and Challenges in Student Recruitmenten_US
dc.typeConference paperen_US
dc.date.dateAccepted2025-05-20-
dc.identifier.doihttps://doi.org/10.1007/978-3-032-07370-9_37-
dc.relation.isPartOfCommunications in Computer and Information Scienceen_US
pubs.finish-date2025-05-30-
pubs.publication-statusPublished-
pubs.start-date2025-05-29-
pubs.volume2670 CCIS-
dc.identifier.eissn1865-0937-
dcterms.dateAccepted2025-05-20-
dcterms.issued2025-10-21-
dc.date.updated2026-11-05T10:25:30Z-
dc.contributor.orcidAlthonayan, Abrahim [0000-0003-3083-5124]-
Appears in Collections:Department of Strategy, Entrepreneurship and Management Research Papers *

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FullText.pdfCopyright © 2026 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is a pre-copyedited, author-produced version of a book chapter accepted for publication in Dhoska, K., Spaho, E. (eds) AI and Digital Transformation: Opportunities, Challenges, and Emerging Threats in Technology, Business, and Security. ICITTBT 2025. (Communications in Computer and Information Science, vol 2670), following peer review. The final authenticated version is available online at https://doi.org/10.1007/978-3-032-07370-9_37 (see: https://www.springernature.com/gp/open-science/policies/book-policies).394.12 kBAdobe PDFView/Open


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