AI Is Hitting the Sweet Part of the S-Curve

One of the most compelling theories about the future of artificial intelligence comes, oddly enough, from a 161-year-old paper about the coal industry. In 1865, the English economist William Stanley Jevons observed that improvements to the coal-fired steam engine had not reduced Britain’s coal consumption. Instead, they had massively increased it. Improved efficiency lowered the cost of steam power, which created so many new uses and users that total consumption skyrocketed. This became known as the Jevons Paradox.

Microsoft CEO Satya Nadella invoked it after DeepSeek launched its low-cost AI model early last year, and the numbers bear him out. According to Epoch AI, the price of running a large language model at a given performance level has been dropping at a median rate of 50x per year. And yet OpenAI’s annualized revenue went from $2 billion in 2023 to more than $20 billion in 2025, while its computing capacity tripled in a single year. Costs are collapsing. Spending is exploding. This is the Jevons Paradox in action.