AI tutoring systems ranges from intelligent tutoring systems to large language model–based conversational agents. These systems are rapidly entering STEM classrooms while their implications for math-based courses such as Operations Research (OR) education remain underexplored. OR courses present unique pedagogical challenges including multi‑step algorithmic procedures, abstract mathematical structures, and complex modeling tasks that require both conceptual understanding and procedural fluency. This paper investigates the emerging opportunities and challenges of integrating AI tutoring into OR education. The main goal of this paper is to identify how AI tutors can enhance personalized guidance, modeling support, visualization, and scalable feedback and highlight critical risks such as mathematical inaccuracies, over‑reliance, explainability gaps, equity concerns, and academic integrity issues. This research also outlines required design principles for effective and trustworthy AI tutoring that match best with requirements and certain specifications of the Operations Research course.