Author's: Raed Atef
Affilation: Independent Researcher Palestine
Volume 1, Issue 1, 2026 | Pages: 1–17 |
Google scholar link → Download PDFThe rapid advancement of generative artificial intelligence (AI) is transforming knowledge management (KM) practices within knowledge-based organizations (KBOs), creating new opportunities for knowledge creation, sharing, storage, and utilization. This study examines the integration of generative AI into KM in the United Arab Emirates (UAE), with a particular focus on the technological, organizational, and contextual factors that shape adoption and effectiveness. Using a mixed-methods approach, the study draws on qualitative thematic analysis of secondary data, including government AI strategies, organizational reports, industry publications, and peer-reviewed literature, to identify the key dimensions influencing AI-enabled KM. To strengthen the conceptual framework, a deep learning model was employed to operationalize relationships among five UAE-specific AI–KM sources and three evaluative criteria, providing an illustration of the framework’s internal coherence and relative significance. The findings indicate that successful AI-enabled KM depends on the alignment of technological infrastructure, human capital capabilities, organizational culture, leadership commitment, and regulatory support. The analysis further reveals that UAE-specific conditions, including national AI initiatives, public–private collaboration, workforce diversity, and the prominence of small and medium-sized enterprises (SMEs), significantly influence organizational adoption pathways. The machine learning assessment highlights that technological readiness alone is insufficient to ensure KM success, as misalignment between technical and social subsystems can undermine organizational performance and knowledge outcomes. By integrating the Knowledge-Based View (KBV), Socio-Technical Systems (STS) theory, and Technology Acceptance Models (TAM/UTAUT), this study proposes a contextsensitive framework that advances understanding of generative AI adoption in emerging economies and provides practical guidance for policymakers, organizational leaders, and KM practitioners seeking responsible and effective AI implementation.
Knowledge Management, Generative AI, Knowledge-Based Organizations, Machine Learning Illustration, Socio-Technical Systems
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