Integration of Artificial Intelligence in Management Information Systems for Optimization of Operations in the Quick Service Restaurant Industry: Systematic Literature Review

Abstract

This study aims to analyze the integration of Artificial Intelligence (AI) into Management Information Systems (MIS) to optimize operations in the Quick Service Restaurant (QSR) industry. The method used was a Systematic Literature Review (SLR) using literature sources from Google Scholar and DOAJ, covering publications from 2016–2026. The study results indicate that the application of AI in MIS and Supply Chain Management (SCM) can improve operational efficiency, decision-making accuracy, and business process optimization through the use of technologies such as machine learning, predictive analytics, natural language processing (NLP), and chatbots. AI also supports real-time inventory management, more accurate demand forecasting, and improved service quality. However, the study findings also identified several gaps, including limited comprehensive empirical evidence, a lack of studies on customer service aspects, a lack of quantitative data, and challenges related to ethics, data privacy, and human resource readiness. Therefore, further, more in-depth and comprehensive research is needed to ensure optimal, sustainable, and operational performance-oriented AI implementation in the QSR industry.