To feed a growing global population under extreme climate pressures, agricultural R & D must move faster than ever. At Corteva Agriscience, Vision AI serves as a critical catalyst to accelerate discovery, transforming how we evaluate seeds, traits and crop protection. However, scaling computer vision from controlled lab environments to unpredictable field conditions on edge and cloud presents significant business and technical bottlenecks. In this session, we will explore the “deployment-first” mindset required to generate real ROI from agricultural vision systems. Attendees will learn the market drivers behind agtech AI, the economic trade-offs of edge versus cloud computing and how automated phenotyping, self-supervised and few-shot learning are slashing time to market. Finally, we’ll share hard-won lessons learned from deploying computer vision at a global scale and highlight the unmet needs where the embedded vision industry can help drive future agricultural breakthroughs.