Satya Nadella argues that AI isn’t just another digital tool—it rewrites how firms learn, innovate and protect their edge. In past shifts, we used software to boost human work. Now AI creates a feedback loop: people train models, models return insights, people learn again. The real battle won’t be over who has the fanciest large model but who builds a system that compounds firm-specific know-how. Nadella calls that “token capital”—the AI you own—and pairs it with human capital’s judgment, relationships and pattern-spotting. Each side lifts the other: without humans to set goals, AI just cycles through data; without AI, human expertise scales too slowly. To capture this compound effect, companies must turn workflows and institutional memory into agentic systems that improve with every use. Private evaluation environments should judge models by internal outcomes—sales lift, error reduction—rather than public benchmarks. Reinforcement loops fed by real transaction traces and judgment logs make each version stronger. Swap out a general model tomorrow, and the firm veteran’s expertise stays intact. That learning loop becomes the firm’s prime asset: a hill-climbing machine that gathers tacit knowledge and accelerates innovation. Nadella warns that if value concentrates in a handful of AI providers, entire industries could repeat the hollowing-out of early globalization. He urges building an ecosystem where every company retains control of its AI-driven learning loop. The goal: broad value distribution across sectors and geographies so employees see their expertise amplified, firms grow uniquely, and the economy gains from continuous, decentralized innovation.