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- The Swimlane survey finds that many businesses aren’t keeping on top of AI’s energy needs
- Almost three quarters are aware of the dramatic energy demands required to train AI models
- Only 13% actively monitor AI energy consumption, which can indicate the most used facilities off-site
As the transition from simple algorithms to advanced models significantly increases energy demand, the adoption of agentic AI, known for its advanced decision-making capabilities, intensifies concerns about energy consumption, the new research stated.
A survey by SambaNova Systems, sampling more than 2000 business leaders from the United States and Europe, found that 70% of business leaders are aware of the substantial energy requirements for training models to AI toolsbut only 13% monitor the energy consumption of their AI systems.
At the same time, 37.2% of companies face increasing pressure from stakeholders to improve energy efficiency, and 42% expect these demands to intensify.
Challenges with AI energy demands
Rising energy costs have become a significant challenge, with 20.3% of companies identifying it as an urgent problem.
Fortunately, 77.4% of businesses are actively exploring ways to reduce energy use 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 companies vulnerable to rising costs and sustainability pressures.
“The results reveal a stark reality: companies are rushing to adopt AI, but are unwilling to manage its energy impact,” said Rodrigo Liang, CEO of SambaNova Systems.
“Without a proactive approach to more efficient AI hardware and energy consumption, especially in the face of growing demand from AI workflows, we risk undermining the very progress that AI promises to deliver,” he added.
“By 2027, my expectation is that more than 90% of executives will be concerned with the power demands of AI. As companies integrate AI, they will address energy efficiency and infrastructure readiness will be essential for long-term success.”
