Artificial intelligence integration as strategic organisational adaptation: faculty evidence from universities in Saudi Arabia and the United Kingdom

Almoraish, Ahmed ORCID: https://orcid.org/0000-0002-4724-9204, Alhakimi, Wail, Abdullah, Ahmed and Al-Mamary, Yaser Hasan 2026. Artificial intelligence integration as strategic organisational adaptation: faculty evidence from universities in Saudi Arabia and the United Kingdom. Technology Analysis and Strategic Management 10.1080/09537325.2026.2711838

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Abstract

Artificial intelligence (AI) is reshaping service practice and increasing pressure on universities to align professional education with emerging technological capabilities. Yet limited research explains how faculty convert changes in AI-enabled services into curriculum integration. This study examines AI integration in services marketing education in Saudi Arabia and the United Kingdom. Drawing selectively on the Technology Acceptance Model, the framework incorporates consumer expectations of AI-driven services, faculty attitudes, institutional readiness, perceived usefulness, curriculum relevance perception, AI literacy and cultural orientation. Data from 231 faculties were analysed using partial least squares structural equation modelling. All seven constructs had significant direct effects on AI integration. However, the proposed indirect effects through perceived usefulness and curriculum relevance perception were unsupported. AI literacy negatively moderated the relationship between curriculum relevance perception and integration, while the remaining interaction effects were not significant. Most path differences were nonsignificant, with differences detected for three relationships. The study positions AI integration as an organisationally situated curriculum decision in which perceived usefulness operates alongside professional and organisational influences. It distinguishes organisational feasibility, pedagogical utility and disciplinary legitimacy, while conceptualising AI literacy as both implementation capability and evaluative filter. The findings inform curriculum review, faculty development and procedural support.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Business (Including Economics)
Publisher:	Taylor and Francis Group
ISSN:	0953-7325
Date of First Compliant Deposit:	5 August 2026
Date of Acceptance:	23 July 2026
Last Modified:	05 Aug 2026 09:30
URI:	https://orca.cardiff.ac.uk/id/eprint/188741

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