The Integration of Artificial Intelligence (AI) Tools and Adaptations in Enhancing Product Quality and Productivity in the Middle East and North African (MENA) Region: A Review

Aluvihara S, Pestano-Gupta F, Hkoma MAB, Karimkhani M, Khalifa ZA, Hamdi MS and Pashtoon R

Published on: 2026-08-04

Abstract

The rapid diffusion of artificial intelligence (AI) tools across manufacturing and service sectors has emerged as a pivotal catalyst for elevating product quality and operational productivity in the Middle East and North African (MENA) region. While traditional industrial strategies in the region have historically relied on labor intensive processes and modest automation, recent strategic policy initiatives such as the United Arab Emirates’ National AI Strategy 2031 and Saudi Arabia’s Vision 2030 have incentivized the integration of machine learning, computer vision, and predictive analytics into core production workflows. Empirical evidence indicates that AI driven defect detection systems can reduce scrap rates by up to 40?% and that adaptive scheduling algorithms improve equipment utilization by 25?% in petrochemical and textile complexes. Moreover, the heterogeneity of MENA economies, spanning high-tech hubs in Qatar to agrarian supply chains in Morocco, creates a natural laboratory for assessing how contextual factors data availability, workforce digital literacy, and regulatory environments influence the efficacy of AI adoption. Consequently, a nuanced examination of AI diffusion mechanisms is essential for scholars seeking to delineate the pathways through which intelligent technologies translate into measurable enhancements in product quality and productivity.