AI for Business Analytics and Operations: Value Creation and Scaling

This course teaches students how AI can support advanced analytics and augment operational decision making across industries. It follows a fundamental business analytics framework: predictive analytics informs prescriptive analytics. Students first build foundations in forecasting (predictive analytics) and optimization (prescriptive analytics), then learn how AI, especially generative AI, can enhances these capabilities. The course then examines two core operational contexts: process improvement and supply chain management. Throughout, students critically evaluate when AI adds value, when it fails, and why human judgment and domain expertise remain essential. Designed for upper-level undergraduate and MBA students, the course requires prior coursework in Business Statistics and Operations Management, as well as working proficiency in R and Excel; coding experience is beneficial. Learning takes place through lectures, case studies, and hands-on analytical exercises. Students will gain practical experience solving business challenges with AI support, develop a deeper understanding of AIs strengths and limitations, and appreciate the importance of human-in-the-loop decision making.Prerequisites: Prior to this registering, students are required to have taken a course in statistics, BZAN1135 (undergrad) or BZAN7703(MBA), and a course in operations management, BZAN1021 (undergrad) or BZAN7700/7720 (MBA).