What Becomes Scarce When Intelligence Abounds?

I have been working with and learning from George Gilder for more than 40 years, and I still remember the first thing he taught me about economics.

It was “wires and switches.” In “Microcosm,” which I edited, he described the economics of the old Bell System. Almost since the invention of the telephone, the most expensive part of the network had been not the wires, but the switches, long dominated by human operators and then by clumsy mechanical devices.

Then, at Bell Labs, the transistor was invented, and everything flipped. Suddenly, switches became the “defining abundance” of the system. Once to be conserved, now the path of wisdom was to “waste” the switches and conserve the wires. So abundant were the switches that they would become computers, infinitely more capable than the human operators the transistors had replaced.

Then another flip. Wires became the scarcity, until copper was replaced by optical fiber, vastly expanding bandwidth, which became a new “defining abundance” and gave us the internet.

As the internet and the computer together multiplied data, the new scarcity became data storage, which George christened “storewidth.”

When one scarcity becomes an abundance, a new scarcity is created.

When switching became cheap, we placed more calls. When compute became cheap, we wrote more software. When storage became cheap, we kept everything. When bandwidth became cheap, we filled it with video.

This is the tale of economic growth. We spend freely what is abundant, and by doing so, we expose what has become scarce.

Wires and switches were the price system at work. Not in equilibrium, but in motion. Technology makes one thing cheap. We use it freely. And in doing so, we discover—through rising costs, delays, and failures—what is still scarce.

The new scarcity becomes the realm of potential profit—until it too is transformed into an abundance. The map of scarcity is not fixed. It is continuously redrafted. And the key to the map is the price system.

Today, the map is being redrawn by artificial intelligence (AI).

For years, compute was the obvious constraint. Training large models required enormous capital, specialized hardware, and time. That constraint is, if not vanishing, loosening under the combined force of scale, better architectures, and relentless iteration.

Now the question is: what becomes scarce because AI becomes abundant?

There is more than one possibility. As models proliferate, high-quality data becomes more valuable. As outputs multiply, verification and trust become binding constraints. As capabilities expand, integration into real workflows becomes the hard part. And as inference scales, memory bandwidth, power, and latency begin to matter as much as, or more than, raw compute.

Consider Nvidia (NASDAQ: NVDA). It is widely seen as the prime beneficiary of AI because it sells compute. That is true as far as it goes. But as graphics processing unit (GPU) performance explodes, the binding constraint becomes moving data fast enough to keep the compute busy. High-bandwidth memory, interconnects, and system architecture begin to dominate.

The value is already shifting—from chips to systems, from FLOPS to data movement, from hardware to the full stack. NVIDIA is winning not because it sells abundance, but because it is positioned at the new scarcity: coordinating that abundance.

This is where investors tend to get tripped up. They look at the layer that is becoming abundant and assume it will be commoditized, that profits will disappear. Sometimes they do—at that layer. But the profits don’t vanish. They migrate, often to places less visible at the outset. Not the headline technology, but the control points around it. The tools that make it usable. The systems that make it reliable. The interfaces that make it accessible.

If intelligence becomes abundant—if generating answers, writing code, and producing analysis becomes cheap—then the scarce resource will not be intelligence at all, but what intelligence cannot replace.

AI can generate recommendations. It cannot bear consequences. It cannot take responsibility. It cannot be accountable.

In a world of abundant intelligence, the scarce resource becomes the willingness to act—and to be accountable for that action. Who signs off? Who takes the risk? Who owns the decision?

Responsibility cannot be outsourced.

The investors who win are not the ones who chase the abundance. They are the ones who identify—early—where the constraint is going next. And the next constraint is humans, who accept responsibility and become even more valuable in an AI world.