AI native biotechs operate on rapid, compute driven design cycles that require high quality experimental data to train and refine their models. This session explores how CROs serve as essential partners by providing the scalable chemistry, biology, automation, and data standards needed to sustain these closed loop workflows. We will outline what truly differentiates AI first companies from traditional biotechs and how integrated CRO platforms act as their external wet lab engine—enabling faster iteration, greater scalability, and more efficient translation of algorithms into drug candidates.