Commoditization

Some products are so special that customers want that exact one brand. Others are interchangeable: gasoline, sugar, memory cards. You buy wherever it’s cheapest, because the goods are the same everywhere. This exact transition from special to interchangeable product is called commoditization. The word comes from the English “commodity,” which roughly means mass-produced good or raw material. In the tech industry it describes a process that almost always runs in the same direction: what counts as a sensation today is standard within a few years, delivered by many providers at a low price.

What happens when AI becomes a commodity

For companies, commoditization is a serious threat. Whoever has a unique product can charge high prices. Whoever has an interchangeable product competes only on price. The profit margin shrinks, and eventually there’s hardly anything left.

This is exactly what has been debated about AI language models for some time now. Such models are programs that write texts and answer questions. At first there were only a handful of them, and they cost a lot of money per request. By now, several companies offer similarly good models. Usage prices have fallen by more than 90 percent within a few years.

For users this is good news, for investors not necessarily. A company that pumps billions into development has to earn that money back. If a free competing model can do almost the same thing shortly afterward, that becomes difficult. That’s why headlines immediately appear with every strong new model, asking whether the industry is currently losing its pricing power.

The path from special case to standard ingredient

Commoditization usually follows a recognizable pattern. At first, only one provider masters a difficult technology. Then others understand how it works and replicate it. Once the knowledge is public, the barriers for imitators drop sharply.

With AI, several factors accelerate this process. Many research findings are freely published as academic papers. On top of that, there are open models whose blueprint and building blocks anyone may download. Whoever builds on that saves a large part of the development work. In addition, a small model can be trained on the answers of a large one, which shrinks the gap even further.

One detail is often overlooked: commoditization does not mean that the technology is cheap to build. Operating large data centers remains expensive. Only the market price becomes cheap, because providers undercut one another. It is exactly this gap between high costs and falling prices that makes the situation dangerous for some companies.

Commoditization in headlines and in your own phone

The term appears regularly in business news. When a Chinese lab releases a model that keeps pace with expensive US models, tech stocks promptly fall. Analysts then write that the base model is becoming a commodity. What they mean is: pure language capability alone is no longer a competitive advantage.

You experience the effect yourself, too. AI features are now built for free into search engines, phone cameras, and text programs. A few years ago, an automatic translation of this quality would have been a standalone paid product. Today it’s a side feature that nobody talks about anymore.

Companies fight back against this development by offering something that can’t be copied. That can be exclusive data, a large user base, or deep integration with a company’s other programs. Commoditization is therefore rarely the end of an industry. It merely shifts where the money can be made.