Technology Is Becoming an Asset Class

Markets know how to price companies. They still struggle to price the technology inside them.

A biotechnology company may depend on one drug. A semiconductor company may depend on one manufacturing process. An AI company may rise or fall based on inference cost, model performance, or access to compute. The company is traded as one financial object, even when most of its value comes from a specific technical capability.

Technology already has many features of an economic asset. It has a cost to create, evidence of performance, a useful life, dependencies, risks, and an expected stream of future value. Its quality can improve or deteriorate. Its value changes when new evidence arrives.

Yet technical progress is rarely expressed in a form that capital can compare directly.

Each industry speaks its own language. AI is measured through capability, reliability, energy use, and cost. Semiconductors are judged by yield, density, efficiency, and failure rates. Drugs move through safety, efficacy, clinical endpoints, and regulatory decisions. Batteries have energy density, degradation, cycle life, and manufacturing cost.

These measures describe different technologies, but they answer the same economic questions. Does it work? Can the result be reproduced? Can it scale? What does each unit cost? What could make it fail?

A measurable technical result often creates value before the financial outcome appears.

A drug reaching a clinical endpoint changes the value of the underlying program. A fabrication process achieving higher yield changes the value of its manufacturing capability. A fall in inference cost changes the value of an AI system. A battery retaining capacity beyond a defined number of cycles changes the value of its chemistry.

Technical outcomes can therefore be understood as economic events.

The probability of a drug succeeding in Phase II, a semiconductor process reaching commercial yield, or an AI model crossing a performance threshold at a viable cost contains real financial information. Scientists, engineers, suppliers, regulators, customers, and investors each see different parts of that probability.

The same logic applies across industries. AI compute can be understood through capability delivered per dollar and watt. Biotechnology productivity can be viewed through the cost and probability of moving from a target to an approved therapy. Semiconductor progress can be tracked through yield, performance, and capital intensity. Energy technology can be compared through output, durability, and operating cost.

This does not mean reducing science to one score. A technology may be scientifically strong but impossible to manufacture. Another may scale well but remain uneconomic. Maturity, reproducibility, scalability, safety, and economic viability are separate dimensions. Preserving those differences is what makes the analysis useful.

Technology becomes an asset when its claims, evidence, performance, risks, and economic rights can be understood consistently over time.

Companies will remain important. Stocks will remain important. But beneath both sits the technical progress that creates, destroys, and redistributes economic value.

Technology may already be an asset class. Markets have simply been pricing it indirectly.