Higher education course designers and instructional leaders are increasingly exploring how AI can support online course redesign, but guidance emphasizes structured, risk-aware implementation. Coverage focused on practical questions for teams deciding where AI fits in redesign workflows and how to evaluate learning gains without defaulting to automation of high-stakes content. The discussion ties AI’s role to instructional design decisions such as assessment alignment, content development and student-facing support—areas where educators must preserve human judgment and accountability. It also reflects broader institutional pressures to modernize learning experiences while protecting academic integrity. For universities, the key operational theme is that AI adoption needs to be treated as a redesign project, not a tool swap: teams must define objectives, map AI-enabled activities to learning outcomes, and establish review processes to catch errors. As adoption accelerates, the article signals a need for clearer institutional policies on transparency, data handling and verification of AI-produced materials in online contexts.