This course develops the methodological capacity to design rigorous interdisciplinary research addressing AI-related organizational and professional problems. Students synthesize AI and technical research with relevant organizational, strategic, or domain literature to identify an unresolved problem and a defensible intended contribution to knowledge and AI practice. They compare quantitative, qualitative, mixed-methods, and design science approaches; justify a research design; and plan sampling, measurement or data collection, analysis, and research ethics. A bounded analytical exercise develops interpretation of findings, validity, and limits of inference. The course culminates in an applied research plan and methodological defense connecting AI research, strategic decision-making, and enterprise execution. It prepares students for the dissertation sequence, where the original contribution is developed and assessed, and remains distinct from the formal dissertation proposal and defense.