Technological revolutions do not repeat themselves, but they do follow patterns. Today, the world is trying to make sense of artificial intelligence (AI), and most of the excitement is focused on model performance, GPU supply constraints, and the staggering scale of training runs. It is very similar to another moment in history when society became captivated by the machinery of a new power source: the rise of electricity starting in the late nineteenth century.
The parallels are not superficial. Electrification, like artificial intelligence today, was a General Purpose Technology (GPT). It reshaped entire economies, reorganized industries, and penetrated every corner of life. Yet, the way people talked about electricity in the beginning was very different from the way electricity ultimately changed the world. The early story was about turbines, dynamos, and the engineering feats inside central stations. The real story turned out to be the systems and applications that used electricity to reorganize society.
Understanding this historical shift helps explain where the value will concentrate in the intelligence age, and why so much of today’s AI debate is centered on the wrong layer of the stack.
The Allure of the Dynamo
When Pearl Street Station opened in 1882, most people had never seen electric light in their homes or workplaces. Located in lower Manhattan, it was the first commercial central power station to supply electricity to paying customers. Newspapers described the plant’s enormous steam engines, its banks of dynamos, and the underground copper network that carried power to businesses and households. Public attention centered on the machinery itself.
Engineers debated generator designs, performance curves, and the technical limits of electrical transmission, which soon erupted into the famous War of the Currents between the proponents of Edison's DC and Westinghouse's AC. Investors believed that the companies building the most advanced dynamos would control the future of industry. Is this starting to sound familiar?
Meanwhile, the real transformation was happening elsewhere. Electricity did not matter because generators improved. It mattered because electricity changed how people lived and worked. Factories redesigned their workflows once each machine could run on its own motor rather than relying on a single steam shaft. Cities changed their patterns of movement once streets could be lit safely after dark.
Households changed their daily routines once electric appliances replaced hours of manual labor. The true power of electricity emerged only when it began reshaping industrial activity, public life, and domestic work. That was the real transformation, because it turned a scientific achievement into a practical force that altered human behavior at every level.
The Economic Pattern of General Purpose Technologies
The companies that built the turbines and dynamos were essential, but they did not become the dominant institutions of the electrical age. Their machinery eventually became standardized, accessible, and inexpensive. The real economic power shifted upward into the systems that coordinated and applied the electricity.
Factories that redesigned production around distributed motors, cities that extended commercial life after dark, and households that reorganized domestic labor around electric appliances became the true platforms of transformation. These environments converted electricity into productivity, safety, and convenience at scale.
The pattern was clear: the substrate became abundant and low-cost, the infrastructure remained necessary, but low margin, and the long-term leverage belonged to the systems that structured human activity around the new capability.
Applying the Lesson to the Intelligence Age
The intelligence age is following the same structural path as electrification. Today, most public attention is focused on the machinery of intelligence. GPU counts are monitored with the same intensity that railroads once tracked steel tonnage.
Benchmark scores are celebrated in the same way as new turbine efficiencies were announced. Each foundation model release is treated as if it will single-handedly determine the future of the economy. This fascination is understandable, but history suggests that it is directed at the wrong layer.
Intelligence, like electricity, is becoming abundant, inexpensive, and increasingly interchangeable. Model performance is converging. Prices are falling. Open source systems are improving fast enough to force commercial providers to reduce costs. These are the signs of a substrate moving toward commoditization. The underlying capability remains important, but it will not be the place where long-term economic power resides.
The real transformation of the intelligence age will emerge from the systems that use intelligence to reshape human work and institutional behavior. I call this the “interface layer” of the intelligence economy: the software environment where workers, supervisors, synthetic agents, and organizational processes meet. It plays the same role that industrial systems, electrical applications, and urban infrastructures played during electrification. It is the point where raw power becomes practical capability.
Most software tools today are still vertical. They monetize a narrow set of functionalities, but they do not exist in one unified environment. Organizations still move through dozens of disconnected systems every day, much like early electrical adopters who combined separate motors, lamps, and generators before standardized architectures appeared. The world has not yet created the horizontal work platform that will become the operating environment for the intelligence age.
That platform will be the place where intelligence becomes productivity. It will bring all core functionalities into one environment and allow synthetic agents to operate alongside human workers on the same plane. It will become the digital body of the organization, rather than another tool on the side. And it will hold the economic leverage that lower layers of the stack cannot capture.
The Actual Beginning
This is the central lesson of any General Purpose Technology. Early attention to technical machinery is normal, but machinery does not become the long-term center of the economy. The substrate becomes ubiquitous and loses pricing power. The infrastructure remains essential but low margin. The systems that organize and apply the capability become the true engines of transformation.
Electricity did not change the world because someone built a more efficient dynamo. It changed the world because factories, cities, and households reorganized themselves around the new power source. Artificial intelligence will not change the world because someone trains a better model. It will change the world because organizations reorganize themselves around intelligence.
The critical question is not which model dominates. It is which systems will apply intelligence in a way that restructures work, institutions, and human coordination. OpenAI and Anthropic are today’s General Electrics and Westinghouses. They are essential, infrastructural titans that built the dynamos, but not the owners of the Intelligence Age itself. That ownership and long-term leverage will belong to the platforms that finally restructure work at the Interface level. That is where the real competition will emerge, and where the long-term value will concentrate. That is the actual beginning of the intelligence age.