Bridging AI Skills Gaps in Marketing Education: Prompt Engineering as a Key Competency
dc.contributor.author | Torkestani, MS | |
dc.contributor.author | Dose, D | |
dc.contributor.author | Mansouri, T | |
dc.date.accessioned | 2025-05-01T13:32:56Z | |
dc.date.issued | 2025 | |
dc.date.updated | 2025-05-01T12:03:22Z | |
dc.description.abstract | The advancement of artificial intelligence is reshaping the marketing landscape, underscoring the need to integrate prompt engineering into marketing education. This study presents a conceptual framework for embedding prompt engineering within marketing curricula, rooted in established educational theories. An integrative literature review and thematic analysis revealed five critical themes: the essential role of prompt engineering, key techniques for marketing students, curriculum integration challenges, effective implementation strategies, and wider implications for marketing education. The resulting framework encompasses five core components: foundational AI and marketing knowledge, skill development in prompt engineering, curriculum integration and design, faculty development through interdisciplinary collaboration, and ethical AI use. A workshop-based case study demonstrates how instruction in advanced prompting techniques enhanced content clarity, creativity, and practical AI readiness. Building on these findings, the paper offers actionable recommendations for curricular design, faculty training, hands-on learning opportunities, industry partnerships, ethical considerations, and ongoing assessment. By equipping students with robust prompting skills and ethical awareness, educators can address the evolving demands of AI-driven marketing, ultimately advancing the profession. This comprehensive framework helps institutions modernize their marketing programs, fostering graduates prepared for innovation and responsible AI engagement. | en_GB |
dc.identifier.citation | Awaiting citation and resolution of DOI | en_GB |
dc.identifier.doi | https://doi.org/10.1080/10528008.2025.2501788 | |
dc.identifier.uri | http://hdl.handle.net/10871/140889 | |
dc.language.iso | en | en_GB |
dc.publisher | Routledge | en_GB |
dc.rights.embargoreason | Under temporary indefinite embargo pending publication by Routledge. No embargo required on publication | en_GB |
dc.rights | © 2025 The author(s). For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. | en_GB |
dc.subject | Artificial Intelligence | en_GB |
dc.subject | Prompt Engineering | en_GB |
dc.subject | Large Language Models | en_GB |
dc.subject | Advanced Prompting Techniques | en_GB |
dc.subject | Marketing Education | en_GB |
dc.title | Bridging AI Skills Gaps in Marketing Education: Prompt Engineering as a Key Competency | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2025-05-01T13:32:56Z | |
dc.identifier.issn | 1052-8008 | |
dc.description | This is the author accepted manuscript. | en_GB |
dc.identifier.eissn | 2153-9987 | |
dc.identifier.journal | Marketing Education Review | en_GB |
dc.relation.ispartof | Marketing Education Review | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | en_GB |
dcterms.dateAccepted | 2025-04-22 | |
dcterms.dateSubmitted | 2024-12-04 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2025-04-22 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2025-05-01T12:03:24Z | |
refterms.versionFCD | AM | |
refterms.panel | C | en_GB |
exeter.rights-retention-statement | No |
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Except where otherwise noted, this item's licence is described as © 2025 The author(s). For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.