The podcast explores how multi-agent AI systems are transforming enterprises by orchestrating workflows across departments and tools. These systems extract context from data and human activity to coordinate tasks, replacing linear processes with parallel, intelligent execution. Key enablers include unified data layers, AI-native architectures, and defensible vertical applications that leverage proprietary feedback loops. Early adopters in finance and insurance are already seeing gains in efficiency and revenue, with AI not only reducing costs but also improving outcomes through continuous learning. Human oversight remains critical to prevent cascading failures, while trust and integration challenges persist. The new operating model shifts power toward companies that can build coordinated agent teams within secure, scalable environments—turning AI into a strategic layer that drives commercial advantage rather than just incremental improvement.