AI energy efficiency monitoring ranks low among enterprise users, survey by inference CPU specialists finds
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High awareness of AI energy demands contrasts with limited actionable solutions. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. As the transition from simple algorithms to advanced models significantly increases energy demands, the adoption of agentic AI, known for its advanced decision-making capabilities, is intensifying concerns over energy consumption, new research has claimed.
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A survey by SambaNova Systems, sampling over 2000 business leaders from the United States and Europe, found 70% of business leaders are aware of the substantial energy requirements for training models for AI tools, but only 13% monitor the power consumption of their AI systems.
At the same time, 37.2% of enterprises are facing growing stakeholder pressure to improve energy efficiency, and 42% expect these demands to intensify. Rising energy costs have become a significant challenge, with 20.3% of businesses identifying them as a pressing issue.
Thankfully, 77.4% of businesses are actively exploring ways to reduce power usage by optimizing their models, adopting energy-efficient hardware, and investing in renewable energy solutions. However, these efforts are not keeping pace with the rapid expansion of AI systems, leaving many enterprises vulnerable to rising costs and sustainability pressures.
