The productivity lag from AI reveals competing logics: automation that replaces labour to cut costs versus augmentation that expands capability to create value. For innovation ecosystems, this choice is existential. Strict safety regulations risk creating moats favouring large incumbents, while unrestricted deployment threatens research quality. The narrow path requires public interest AI infrastructure, risk-weighted governance, and incentives rewarding high-impact discovery