Volume 6 - Issue 16 (2026-07-02)

The Impact of Artificial Intelligence in Supply Chain Management on Logistics Efficiency in Saudi Arabia

Dr: Raed Abu Alkhair

Washington Center: Washington- District of Columbia-US

Saudi Vision 2030 considers the logistics industry an important strategic goal in diversifying the country’s economy and the National Industrial Development and Logistics Program aims to connect the national economy to international trade via advanced digitized supply chain networks. In order to achieve this transformation, artificial intelligence is identified as a key technology to improve the industry, with several technologies in its toolkit, like machine learning, demand forecasting, Internet of Things, and machine vision and object detection for inventory management.

Despite the abundance of empirical studies on artificial intelligence in different sectors, like the telecommunications, pharmaceuticals, and manufacturing industries in Saudi Arabia, there is very little quantitative analysis on the impact of artificial intelligence in Saudi Arabia’s logistics sector. Furthermore, the quantitative results presented in the few relevant studies are not generalized enough and are insufficiently represented in the national logistics industry.

This paper presents a meta-synthesis approach in order to answer the question: which artificial intelligence technologies are being utilized within the supply chains of Saudi Arabia and what is their impact on the logistics efficiency measures of cost, speed, accuracy, and resilience? The paper reviews 40 articles and uses 30 articles in the meta-synthesis. This meta-synthesis is presented qualitatively because there are no empirical evidence to present a meta-analysis in quantitative format in Saudi logistics industry.

The meta-synthesis finds that technical, organizational, economic, and social barriers that need to be addressed in order to successfully implement artificial intelligence in Saudi Arabia’s logistics sector. Furthermore, the meta-synthesis reveals that efficiency measures are not well-defined and standardized, preventing comparison in the meta-synthesis. These findings highlight the need to establish standardized measurement benchmarks for artificial intelligence in logistics. The paper concludes by proposing a research agenda that could support decision-making and strategic planning for government and private sector logistics, policy-makers interested in the national adoption of artificial intelligence in Saudi Arabia, and academics interested in this new research field in Saudi Arabia.