APPLICATION OF AI IN LOGISTICS AND SUPPLY CHAIN OPTIMIZATION FOR LOCAL ECONOMIC DEVELOPMENT: A CASE STUDY IN THE MSME INDUSTRY

Abstract

Artificial intelligence (AI) has become an important innovation in improving logistics and supply chain efficiency in various sectors, including the Micro, Small, and Medium Enterprises (MSMEs) industry. However, many MSMEs still face challenges in implementing AI effectively, such as limited costs, technical knowledge, and technological infrastructure. This research aims to analyze the application of AI in logistics and supply chain optimization, as well as its impact on local economic development. The research method uses a mixed approach, namely thematic analysis on qualitative data to understand the constraints and perceptions of MSME actors and descriptive statistical analysis on quantitative data to measure the impact of AI application on logistics efficiency. The results show that the application of AI is able to improve the efficiency of stock management, optimize delivery routes, and reduce distribution costs by up to 20%. However, implementation cost constraints and limited technology infrastructure are still the main obstacles for MSMEs in utilizing AI optimally. The recommendations of this study include technology subsidies from the government and technical training programs for MSME actors so that they can overcome challenges and utilize AI to support local economic growth.