This chapter explores how generative AI is reshaping the academic research lifecycle—from ideation and literature discovery to hypothesis formation, methodological planning, and data acquisition. By enhancing early-stage processes through tools like GPT, Claude, and Gemini, researchers can streamline conceptual development, uncover cross-disciplinary connections, and rapidly synthesize literature. Generative AI assists in hypothesis generation and method selection, offers technical support for coding and data collection, and facilitates integration across tools. However, its value lies not in automation alone but in collaboration: when used critically, these systems enhance scholarly insight without compromising academic rigor. The chapter emphasizes the importance of validation, transparency, and ethical caution in AI-assisted research design.