AI efficiency fuels Jevons Paradox debate over HBM demand

The rising complexity of AI models is reshaping memory demand dynamics. While advancements like GPT-6 enhance computational efficiency per task, the increased frequency of concurrent operations and data exchanges are driving robust demand for HBM and server DRAM. Upstream, NAND and DRAM manufacturers face capacity realignment pressures; downstream, data center operators must rapidly upgrade infrastructure to address bandwidth constraints. Geopolitical tensions, particularly between the US and China, are intensifying supply chain risks, forcing companies to restructure procurement strategies. In response, industry leaders such as NVIDIA, AMD, and SK Hynix may accelerate HBM production capacity or pursue strategic acquisitions to secure local supply chains. Over the next 12–24 months, exponential growth in AI compute demand is expected to trigger a supply shortage in HBM markets, creating a new technology lock-in dynamic.