Smarter Bridges: Leveraging Artificial Intelligence to Reshape University-Industry Technology Transfer

Mohammed Khaouja (), Sanaa Dfouf, Kaoutar Errakha, Hanan Elharissi and Fekkak Hamdi
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Mohammed Khaouja: LRMD FEG Settat - Laboratoire de Recherche en Management et Développement - Faculté des Sciences Economiques et de Gestion, ERMOT - Laboratoire "Etudes et recherches en Management des Organisations et des Territoires" [Fez] - USMBA - Université Sidi Mohamed Ben Abdellah
Hanan Elharissi: FEG SETTAT - Faculté d’Économie et de Gestion de Settat

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Abstract: University-industry technology transfer (UITT) is essential for converting academic research into commercial use, yet traditional strategies often fail to address the knowledge gap. Literature suggests that institutional inertia, communication barriers, and ineffective marketing strategies hinder the commercialization of technology. This study proposes a conceptual framework that incorporates AI-driven marketing to enhance knowledge dissemination, market identification, and stakeholder engagement within the technology transfer process. This systematic literature review amalgamates insights from UITT, AI marketing applications, and knowledge management systems. A qualitative analysis of peer-reviewed literature from 2017 to 2025 identifies trends, deficiencies, and emerging patterns, leading to an integrated framework that assesses technology transfer strategies and the implementation of AI marketing across diverse sectors, leveraging the Technology-Organization-Environment (TOE) model and the Unified Theory of Acceptance and Use of Technology (UTAUT). The investigation demonstrates that AI-enhanced marketing can significantly bolster UITT through five AI-enhanced marketing capabilities: precise client segmentation, predictive analytics of market trends, tailored communication, improved knowledge management, and streamlined digital outreach. This methodology fosters reciprocal knowledge exchanges, positioning AI as a facilitator between market insights and university research aims while refining technology presentations for industry stakeholders. Moreover, the study highlights critical concerns regarding data privacy, implementation expenses, technical complexities, and the necessary proficiency in AI and technology transfer.

Keywords: research initiatives; Collaboration university-industry technology transfer AI-enhanced marketing innovation knowledge sharing economic growth strategic partnerships research initiatives entrepreneurial mindset; entrepreneurial mindset; Collaboration; strategic partnerships; economic growth; knowledge sharing; innovation; AI-enhanced marketing; technology transfer; university-industry (search for similar items in EconPapers)
Date: 2026-06-01
Note: View the original document on HAL open archive server: https://hal.science/hal-05638557v1
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Published in International journal of advanced computer science and applications (IJACSA), 2026, 17 (5), pp.935-949. ⟨10.14569/IJACSA.2026.0170586⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05638557

DOI: 10.14569/IJACSA.2026.0170586

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