Integrating Artificial Intelligence in Autonomous Cashier Systems: A Study on Functional Schema Design and Its Impact on Supermarket Operations

Abstract

This study investigates the integration of artificial intelligence (AI) into autonomous cashier systems, emphasizing functional schema design and the transformative impact on supermarket operations. The research demonstrates how AI technologies like machine learning and big data analytics may improve operational efficiency, reduce human errors, and increase consumer happiness through tailored shopping experiences and quicker checkout processes. The study addresses essential dimensions such as user accessibility, data security, equitable access, and operational efficiency, emphasizing the importance of inclusive and adaptive functional models. Ethical problems, such as data privacy and customer trust, are discussed with the potential socioeconomic consequences of worker displacement and reskilling requirements. Using an integrative literature review, the study combines theoretical and practical insights to propose actionable solutions for successfully adopting AI-driven cashier systems. The findings emphasize the need to balance technical breakthroughs with ethical principles and inclusivity and provide a framework for future research and practical application in retail environments. This study increases our understanding of AI's potential to transform supermarket operations while creating sustainable, customer-centric, and efficient retail ecosystems.

Keywords:

Functional schema design, User acceptance and experience, Operational efficiency, Data security and privacy, Equitable access, Ethical implementation, Inclusive implementation, Technology