Artificial Intelligence–Enabled E-Commerce Systems and Automated Warehousing: Economic Effects from Amazon FBA in the U.S. Market

Abstract

The rapid integration of artificial intelligence (AI) into e-commerce platforms has fundamentally transformed digital trade, supply chain management, and business scalability in the United States. This study examines the economic implications of AI-enabled e-commerce platforms and automated warehousing systems, using Amazon Fulfillment by Amazon (FBA) as a representative case to assess impacts on productivity, small business participation, labor dynamics, and overall economic performance. The analysis explores how AI-driven capabilities such as demand forecasting, dynamic pricing, robotic fulfillment, automated inventory management, and algorithmic advertising enhance operational efficiency, reduce transaction costs, and improve market responsiveness. The findings indicate that AI adoption within the Amazon FBA ecosystem lowers entry barriers for small and medium-sized enterprises, strengthens supply chain resilience, and contributes to higher levels of productivity across the U.S. economy. At the macroeconomic level, AI-enabled e-commerce and warehouse automation support GDP growth, regional economic development, and tax revenue expansion, while reshaping employment patterns through job transformation rather than widespread displacement. Despite these benefits, the study highlights critical challenges related to market concentration, data governance, workforce reskilling, and automation governance. Overall, the paper argues that AI-enabled e-commerce platforms and automated fulfillment infrastructures function as economic multipliers, reinforcing U.S. competitiveness in the digital economy when accompanied by balanced regulatory and policy frameworks.