Media companies are sitting on petabytes of valuable footage, yet most of it remains difficult to search, slow to license, and nearly impossible to structure for AI. At the same time, AI labs are demanding highly specific, rights-cleared video datasets delivered faster than traditional archive workflows can support. In this fireside chat, leaders from Protege and TwelveLabs discuss how multimodal video intelligence is helping transform raw archives into structured, AI-ready video at scale. By replacing manual tagging and metadata searches with precise, natural-language extraction, teams can quickly identify and deliver the exact moments AI systems need. The result: faster deal cycles, reduced operational overhead, and new revenue opportunities unlocked from existing video libraries.