The Criticality-Routing Problem

A systems engineer at a mid-size AI startup requests a quote for server memory to expand a training cluster. The number comes back nearly four times what it cost a year ago. The vendor doesn’t apologize. “Everyone’s paying this now,” they say.

Nobody sorted this demand before it hit the market. That is the actual problem.

The Wrong Debate

There are two popular stories about why AI is making chips, memory, and critical minerals more expensive. One says a handful of companies are price gouging. The other says this is just supply and demand, nothing to examine, wait it out.

Both miss the same thing. Neither one asks who should get priority when a scarce input has ten buyers and only enough supply for three. Right now the answer is whoever bids highest. Every time. No distinction between a hospital ordering one server and a hyperscaler ordering ten thousand.

This is the same failure mode behind our privacy-routing work. Nobody sorts before they route.

Sort First, Route Second — At Global Scale

In query routing, the fix was to classify a query’s sensitivity before picking which model handles it. A drug-interaction lookup and a patient’s lab result are not the same risk class. They should not get the same treatment.

The same logic is missing entirely from the market for AI hardware and materials. A gigawatt of frontier-model training compute and a hospital’s imaging server are not the same criticality class. Today, both compete in the identical open market, against the identical bidders, for the identical wafers.

Call it criticality-routing: sort demand by what’s actually at stake before deciding who gets served, and at what price. Right now, nobody does this — not the chipmakers, not the miners, and only barely, unevenly, the governments now trying.

We don’t have this framework built yet. Nobody does. Here’s why it’s needed.

Why AI Is Making Chips, Memory, and Minerals More Expensive

Apple’s stock took its worst single-day drop in over a year in June 2026, the day after it raised prices across its Mac and iPad line. The company’s own explanation: AI data centers now absorb roughly 70% of the world’s memory chip supply, up from a small share a few years ago. Reports put the price increase for common memory chips at 80 to 90% in a single quarter — the sharpest move the memory industry has ever recorded.

Rare earth magnets tell a similar story with a harder edge. In April 2025, China restricted exports of seven rare earth elements and the magnets built from them. Within weeks, Ford idled an assembly plant for a week for lack of magnets, and its CEO described sourcing as “hand-to-mouth.” A separate dispute over a Dutch-Chinese chipmaker forced production cuts at Honda plants across several countries months later.

Copper is next in line. A single gigawatt of AI data center capacity needs roughly 50,000 tons of it. At the industry’s planned build-out pace, data centers alone will require more new copper every year than the entire world added to supply last year.

None of this is a pricing failure. It is a routing failure. There is no mechanism anywhere that sorts which use of a scarce material matters most before that material gets sold to whoever bids first.

Governments Are Starting to Sort — Just Not Well

After the 2025 shortage scare, the U.S. Department of Defense bought a 15% stake in the only significant rare earth mine in the country and guaranteed it a floor price for ten years. Days later, a major electronics maker put half a billion dollars into the same company.

That’s a government doing a version of criticality-routing: deciding a category of demand — defense and strategic manufacturing — deserves guaranteed access ahead of the open market. It’s also happening with no public framework, no published criteria, and no way for an outside party to check the math.

The same pattern reached AI models directly this year. One frontier model launched on schedule. A competitor stayed limited to a short list of approved organizations. Anthropic’s own most capable models were pulled globally for roughly two and a half weeks under U.S. export controls before access was restored (Anthropic’s statement). Three companies, three outcomes, decided by a process nobody outside government can fully see or audit.

Sorting is happening. It just has no measurement, no transparency, and no consistent criteria — precisely the gap our governance-overhead research exists to close at the query level, and precisely the gap nobody has started closing at the hardware and materials level.

What CARE Does

We don’t have a criticality-routing framework for hardware and materials. Nobody does. But we know what one would need, because we’ve built pieces of a smaller version of the same problem.

It would need a real measurement of what criticality costs to define and enforce — the materials-layer version of the 0.2 to 0.35 milliseconds we measured for query-level governance overhead. It would need open, checkable classification criteria, instead of decisions made behind closed doors. And it would need to reach the people setting policy before the next shortage hits, not after.

That is what CARE does: we measure, we build, we hand the facts to the people who decide. We think this is the next place that discipline needs to go.