DRIVERS AND BARRIERS TO AI ADOPTION IN RETAIL ENTERPRISES: A SYSTEMATIC LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK

The emergence of artificial intelligence (AI) technology has profoundly changed the value chain of the retail industry. However, there is a significant gap between the potential value of AI and its actual implementation in retail operations, which highlights the practical challenges of integrating AI into daily operations. Since the introduction of ChatGPT in 2022, the number of studies on the application of AI technology has surged. This study aims to systematically explore factors that promote and hinder AI adoption in retail businesses. The study employed a systematic literature review, focusing on peer-reviewed academic articles in English published between 2015 and early 2025. This review specifically covers the topics of AI technology. The results of this study identify five major drivers, including cost reduction, improving service quality, marketing activities, external factors, and supporting decision-making. In addition, seven major barriers were identified, including perceived ease of use, uncertainty in returns, lack of talent, digital environment, investment and cost, data privacy and ethics issues, and organization and culture. This study also developed a conceptual framework based on the Technology Acceptance Model (TAM) to describe the mechanisms in which driving and impediment factors take effect. This study assists researchers in assessing the current state of research on AI adoption. As attention to AI technology grows, the importance of integrating evaluations of existing systems becomes evident.