When everyone digs for gold, sell shovels. This old maxim captures the same logic as today’s artificial intelligence boom: the profits are flowing to those supplying the chips and infrastructure, not to the loss-making labs building the models.
Nvidia’s record earnings this past year, which pushed the chip maker’s market value past $5 trillion, show how profitable that trade has become.
But what if the world is selling the wrong kind of shovel? Analysts expect the global build-out of AI infrastructure – from data centres and chips to power and cooling – to cost several trillion dollars over the next few years. Much of that hardware is being built to run large language models (LLMs) such as OpenAI’s ChatGPT or Anthropic’s Claude.
But here’s the rub – if development moves towards smaller or more efficient AI, or if new technology reduces the demand for high-end chips or the large amounts of energy they require, much of that heavy infrastructure could end up underused, even uneconomic. The world is pouring trillions of dollars into one version of AI and risks hard-coding that choice i
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