This chapter provides a practical guide to using generative AI in academia, offering strategies for integrating AI into research, teaching, and administrative workflows. It outlines foundational principles for effective AI use, including prompt engineering, critical evaluation of outputs, and tool selection based on context and discipline. The chapter emphasizes the importance of developing AI literacy—treating AI as a collaborator rather than a replacement—and provides guidance on navigating common limitations, such as hallucinations, citation errors, and shallow analysis. By cultivating adaptable AI skills and applying them thoughtfully, academics can enhance productivity, maintain scholarly integrity, and stay ahead in an evolving technological landscape.