Open-Source AI Adoption Expected to Surge 63% as Costs Drop

JPMorgan cites Jevons Paradox, noting open-weight models lower barriers, driving broader enterprise uptake and sustained demand for NVIDIA infrastructure.

Woofun AI reports that JPMorgan Chase asserts the proliferation of open-weight AI models, including Kimi K3, Qwen, and Llama, will accelerate industry adoption by reducing deployment costs. The bank argues this cost efficiency strengthens, rather than diminishes, the competitive edge of market leaders.

JPMorgan Chase invokes the "Jevons Paradox," suggesting that increased technological efficiency will stimulate greater overall demand for AI services. The institution projects long-term coexistence between open-weight and closed-source architectures, noting that 63% of enterprises currently utilize both. Regardless of the dominant model type, NVIDIA is identified as the primary beneficiary due to escalating demand for AI computing infrastructure.