From Data-Centric AI to Organizational Intelligence: Why Data Quality, Governance, and Human Oversight Determine the Success of AI Adoption in MENA Organizations

Artificial intelligence (AI) adoption is expanding across organizations worldwide, including those in the Middle East and North Africa (MENA). Yet many organizations continue to struggle to translate AI investments into sustained organizational value. This gap has drawn attention to factors beyond model performance, especially the way AI systems are embedded in data practices, governance structures, and decision-making processes. Drawing on recent interdisciplinary literature, this paper examines AI adoption through a data-centric and sociotechnical lens, with particular attention to the MENA context. It argues that successful AI adoption depends less on algorithmic sophistication alone than on the alignment between data quality, governance mechanisms, and human oversight. The paper constructs a conceptual framework illustrating how these elements influence organizational intelligence and the strategic value obtained from AI. The study also proposes four hypotheses about data maturity, governance, human-in-the-loop design, and contextual factors in MENA organizations. By placing AI adoption within larger context of organizational and institutional structures, the study provides a conceptual foundation for future empirical research and for more responsible, context-aware AI deployment in the region.