Tracks vs. Trains: Why the Real Artificial Intelligence Boom Hasn't Started Yet (shawnharris.com)

The AI landscape is poised for significant transformation as it approaches 2026, marking a critical juncture between the "Installation Phase"—characterized by heavy investment in infrastructure—and the anticipated "Deployment Phase," where value creation will shift to practical applications of AI technologies. While the past few years have seen unprecedented capital channeled into building data centers and acquiring GPUs, this phase is reaching saturation, leading to inflationary pressures and an unsustainable ROI gap. This transition highlights the bifurcation of the AI economy into an over-capitalized infrastructure layer and a burgeoning application layer, suggesting that true economic growth will emerge from the latter as businesses leverage this established infrastructure. Analysis rooted in Carlota Perez's theory of technological revolutions indicates that the impending "Turning Point" signals a profound market correction, necessitating institutional recomposition and regulation to stabilize the sector. As the EU AI Act comes into effect, it will guide the recoupling of financial and production capital, paving the way for synergistic growth in the application side of AI—where businesses will build innovative solutions without the burdensome overhead of infrastructure investment. This marked transition is crucial, as the economic potential of AI applications could potentially transform sectors, fueling a "Golden Age" of productivity and innovation, while also addressing the systemic risks associated with circular financing and speculative market practices.