This research paper explores the transformative role of generative artificial intelligence (AI) in facilitating knowledge transfer from research and development (R&D) labs to entrepreneurial markets. Through qualitative analysis of interviews and focus group discussions with entrepreneurs, researchers, and AI experts, the study investigates the mechanisms, trends, and best practices associated with AI-driven knowledge transfer. The findings reveal that generative AI can significantly enhance the discovery, synthesis, and contextual adaptation of scientific knowledge for market applications, accelerating innovation cycles and fostering collaborative ecosystems. The study highlights the potential of AI-powered tools in streamlining ideation, prototyping, and market validation processes, while emphasizing the importance of responsible innovation practices and inclusive governance mechanisms. The research also examines global trends in AI adoption for knowledge transfer, acknowledging the variability across regions due to cultural, regulatory, and infrastructural factors. By providing actionable insights for entrepreneurs, researchers, and policymakers, this study contributes to advancing the understanding of AI-driven knowledge transfer and its impact on entrepreneurial innovation. The paper concludes by emphasizing the need for contextualized strategies and cross-disciplinary collaboration to harness the full potential of AI in bridging the gap between scientific advancements and sustainable business solutions.