The integration of Generative AI (GenAI) in educational settings has piqued the interest of researchers and educators alike, unveiling a myriad of potential applications across various teaching and learning processes. However, introducing and implementing AI tools in classrooms, particularly for assessment and evaluation purposes, presents a significant challenge. Therefore, this chapter delves into the design and application of generative AI in STEM (Science, Technology, Engineering, and Mathematics) Education courses, with a specific emphasis on industrial systems engineering programs. The proposed experiment is structured into two distinct phases: a mathematical optimization phase and a programming modeling phase. The overarching objective is to meticulously measure and evaluate students’ interactions with GenAI tools, their comprehension of the assessments, their ability to develop solutions, and ultimately, their attainment of the targeted learning outcomes. By leveraging the power of GenAI, this chapter aims to explore innovative approaches to assessment and students’ evaluation, fostering a deeper understanding of complex concepts and enhancing the overall learning experience within STEM disciplines. The chapter seeks to provide valuable insights into the efficacy of GenAI tools in facilitating comprehension, problem-solving skills, and the achievement of learning objectives in industrial systems engineering and related fields.