Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrasctructure, Enterprise AI, SaaS

Artificial General Intelligence already exists, yet its impact remains limited because models lack the deep, tacit context trapped within human organizational processes. While the "software is dead" narrative gains traction, software remains vital; however, lower barriers to entry and reduced switching costs demand that companies innovate or risk displacement. Historical technological shifts, such as the transition from steam to electric power, demonstrate that productivity gains require fundamental structural rewiring rather than simple tool replacement. Consequently, the most significant value in the AI era will accrue to applications that successfully integrate proprietary data and specialized workflows, particularly in high-stakes industries like healthcare and education. Rather than chasing speculative superintelligence, organizations should focus on transferring human expertise into silicon to drive tangible, long-term impact.