Who Discovers the Future? AI, Power, and the New Architecture of Science

AI is compressing time between question and discovery, reshaping not only how research is conducted, but who is prepared to participate in AI-enabled innovation. This panel examines the consequences of that shift: how research is evolving, how researchers and students are trained, and how universities and institutions must adapt when much of the “bench work” can now be executed by algorithms. As AI systems compress the distance between hypothesis and discovery, institutions face a new mandate: attracting and developing AI-fluent talent across disciplines, equipping students with the skills to operate within agentic and AI-enabled workflows, and ensuring that breakthrough research moves efficiently from lab to real-world application. We will explore how the architecture of science is changing, how the distinction between builders and users is blurring, and how curricula, incentives, and talent pipelines must adapt to produce a workforce capable not only of generating knowledge, but of applying it responsibly and translating it into economic opportunity, workforce mobility and broader societal impact.