Self-driving laboratories (SDLabs) represent a transformative approach to research and development (R&D), combining artificial intelligence (AI), robotics, and digital tools to revolutionize workflows in deep-tech industries (e.g. materials, chemistry, biotechnology), and beyond. By automating experiments and decision-making processes, SDLabs enable faster and more efficient scientific discovery, reduce costs, and enhance reproducibility. This white paper explores SDLabs' potential, from accelerating innovation to addressing sustainability challenges, while highlighting critical ethical, cultural, and technological considerations. Furthermore, it examines the role of AI in technology transfer, showcasing success stories and actionable strategies for leveraging these advancements across sectors.