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      Demand for Computing Power Expected to Rise Due to Cheaper AI Technologies

      Zach Pandl, the Research Director at Grayscale, highlighted in his recent column that the increasing demand for artificial intelligence (AI) is largely driven by decreasing operational costs and advancements in technology that enable more autonomous task performance. This trend is anticipated to significantly boost the demand for computing power and the necessary physical infrastructure that supports AI applications.

      Pandl noted that the competition among open-source weight models is leading to lower token prices, making AI technologies more economically viable for a wider range of applications. For instance, Anthropic's new Sonnet model claims to reduce task costs by up to 30%, while OpenAI's recently launched always-on agent can work continuously towards user goals, potentially increasing the demand for computing resources.

      Goldman Sachs has projected that by 2030, token consumption could rise by 24 times, primarily due to the use of AI agents. Despite improvements in efficiency, the overall demand for computing power may still escalate if usage grows at a faster rate. Pandl emphasized that digital activities depend on physical infrastructure, such as electricity and data centers, which require time to develop. He also mentioned that CoreWeave has recently entered into new contracts at higher prices for computing power, indicating a tight supply in the market. Ultimately, Pandl concluded that the combination of cheaper AI and more powerful agents could expand usage cases enough to sustain demand for computing power, benefiting its owners.

      © 2026 KLEA News. All Rights Reserved. This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.

      Source: KLEA News

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