The emergence of cheaper and more efficient AI models off the back of China’s DeepSeek could reshape demand for data centers, boosting a sector that investors were already heavily betting would continue to boom.
For years now, analysts have forecast exponential growth in data centers — the critical infrastructure required for powering the world’s digital transition and the training of large language models (LLMs).
China’s startup DeepSeek AI model sent investors in jitters in late January, as the launch of its R1 model raised questions about U.S. dominance in the AI sector and whether the developer’s efficiency gains could dent demand for data center capacity.
Data centers often take at least two years to build and orders have largely already been factored in for 2025 — meaning that the launch of the disruptive R1 model is unlikely to have any immediate impact. While the launch of DeepSeek’s R1 initially led to some analysts tempering their forecasts as they questioned whether money pumped into the sector might have been somewhat “misguided,” experts told CNBC that models built more cheaply and with less powerful chips could ultimately become an accelerant for the market.
Schneider Electric, the most-exposed European firm to data centers according to UBS, lost more than 9%, Siemens Energy shares shed 20% and ABB closed 6% lower on the day.
Some stocks have since recouped their losses, recovering from the knee-jerk reaction from markets. Earnings statements from mega-hyperscales such as Alphabet’s Google and Meta also instilled confidence, as both firms committed to multi-billion dollar investments following the tech sell-off.
There hasn’t been “much room for error” in the sector, said UBS’ Kukhnin. “That’s why some of the stocks have tumbled and are not immediately being bought back, because people already own a lot of the shares and are now trying to figure out whether this is the opportunity to add or if it’s the opposite.”
He added that lower costs indicate a potential democratization of AI, which could lead to an acceleration in the adoption of the technology — which is “something that’s very difficult to quantify.”
The data center market will also continue to be fueled by the digital transition, which takes place separately from advancements in AI. “Generative AI was kind of almost icing on the cake, but has become a very thick layer of icing, certainly in terms of future growth,” Kukhnin said.
Bruce Owen, EMEA president at Equinix, said the firm is “well positioned as the AI technology curve is bent,” adding that he expects the advent of more efficient models to be an “accelerant,” for AI.
“An additional dynamic that we might see is the ‘Jevons paradox,’ which posits that increased efficiencies of a resource can lead to greater consumption of that resource,” he told CNBC.
Ryan Cox, head of AI, at consultation firm Synechron, also expects the Jevons Paradox effect to see more efficient technology ultimately lead to more data center demand.
“It’s a really complex equation,” he told CNBC, noting that there are several headwinds and tailwinds when it comes to determining potential shifts in demand. He shared that Synechron’s clients are pursuing “safe” options to indirectly use DeepSeek, such as via Hugging Face, a repository for AI models.
“Overall, I think that efficiency will fuel adoption, and I think it will continue to push up the usage, even as these costs go down. The race towards these more advanced models and the broader applications, the use of AI, means that the overall data center demand, will rise and not fall,” Cox noted.