a16z 데이터에 따르면 AI 분야에서는 제본스의 역설이 나타나고 있다. 토큰 가격은 계속 하락하지만, AI 가격 인하가 수요를 빠르게 늘리면서 H100 임대 가격은 유지되거나 오히려 상승하고 있다.

Jevons' paradox is Jensen Huang's best friend. Data from Ornn, Silicon Data, and Bloomberg (as of August 2026) shows what a16z calls a textbook Jevons paradox in the AI market. Token prices keep dropping, but H100 GPU rental prices hold steady or climb. Cheaper tokens unlock AI agents, automation, and new applications, so volume grows faster than per-unit costs fall.

How much demand comes from humans versus the systems themselves isn't clear, since agentic AI burns through tokens at a staggering rate. Compute demand could be artificially inflated, and even modest human usage growth could trigger outsized hardware needs.

The whole system rests on one assumption: AI usage has to grow fast enough to offset falling token prices. As long as it does, hardware stays scarce and expensive. If demand flattens, the chain from chip makers and memory suppliers to energy providers and cloud companies takes a hit. Markets could spiral from there, and how sensitive they already are became clear when US stocks dropped on reports that OpenAI's annualized revenue might be lower than previously reported.