Noam Salinger

The Data Problem: What AI Actually Runs On | RAISE Summit 2026

Matt Fitzpatrick, Philippe Mizrahi, Noam Salinger, Molly Presley, Travers Nisbet, Petrina Anne Steele, Petrina Steele, Emily Fortuna

Enterprise AI adoption remains critically hampered by organizational inertia and legacy infrastructure, with only 5% to 8% of projects reaching production while global compute allocation shifts decisively toward 80% inference needs. Leaders must address fragmented data silos and misaligned workflows by implementing global namespaces and human-in-the-loop validation protocols to ensure agents meet strict liability standards. As constraints evolve from pure data quality to energy supply and physical infrastructure, successful transformation will depend on re-engineering business processes rather than merely overlaying new models onto broken systems.