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While the debut of the DeepSeek AI model earlier this week sparked a sharp sell-off in U.S. tech stocks, its gains in AI processing efficiency could have big implications for data centers.
Market darling Nvidia shares fell more than 12% and the Nasdaq fell 2.7%, with analysts saying the reaction reflected concerns about whether huge investments in AI and its infrastructure are justified.
Meanwhile, U.S. power and utility stocks fell sharply on reports that DeepSeek’s model raised questions about expectations of an AI-driven surge in data center power demand.
Any shift toward cheaper, more powerful and more energy-efficient algorithms has the potential to significantly expand the scope of AI applications, which could ultimately drive demand for large-scale and distributed data center infrastructure.
“If the reports about DeepSeek are true, this will only drive AI innovation forward,” said Mitch Lenzi, vice president of sales and operations at Baxtel, an online platform dedicated to directories and reviews of managed data centers around the world.
The new model and reduced deployment costs will enable competitors to optimize their own AI strategies, driving demand and adoption, he said.
Lenzi said he believes AI advances like DeepSeek will ultimately accelerate, not slow, data center growth.
“Innovation in AI doesn’t reduce demand, it drives it,” he said. “As AI becomes more pervasive and cost-effective, the industry will continue to expand, maintaining demand for high-performance data center infrastructure.”
Sean Farney, vice president of data center strategy at JLL, agreed that the introduction of more efficient AI models like DeepSeek could reshape the data center market.
“That’s great news for the industry,” Farney said. “If someone finds a cheaper, more efficient way to do AI, it lowers the barrier to entry and makes AI accessible to a wider audience.”
Over time, that will drive increased usage and create new opportunities for data center growth.
Farney noted that AI GPU-focused data centers are already the fastest-growing segment of the market, with a compound annual growth rate (CAGR) of 39%, nearly double the overall data center growth rate of about 20%.
“AI-focused facilities are growing much faster than traditional data centers,” Farney said. “With innovations like DeepSeek, we may see an acceleration in this space.”
The financial implications of this growth are huge: According to Farney, annual spending on infrastructure by major hyperscale data center operators has soared from $200 billion to $300 billion.
“The industry is booming,” he said. “If technologies like DeepSeek make AI applications faster and easier to deploy, we will need more data centers to support this adoption.”
John Dinsdale, chief analyst and research director at Synergy Research Group, noted that it is generative AI (GenAI) that has led to some data center rethinking and re-architecting.
“If technology emerges that can significantly reduce the required power density, this may mean a return to pre-GenAI designs with more traditional cooling and power distribution,” he said.
Dinsdale explained that there is currently considerable investment in GenAI technology and products across the IT ecosystem, and this situation will not change in the short term.
“Will some technology emerge that can reduce the power consumption and cost of training and running AI models? Absolutely,” he said. “It’s the nature of technology development and lifecycles.”
When costs go down and capabilities go up, that tends to spur big increases in adoption and usage.
“Take the growth of cloud computing services over the past 15 years,” Dinsdale said.
The role of modular and edge data centers
Farney also highlighted the growing importance of small, modular, and edge data centers in this evolving environment.
While training large AI models will still require large centralized facilities, the growing focus on AI inference (using trained models to provide real-time insights) is likely to drive demand for distributed, latency-sensitive edge data centers.
“As we move into the inference phase of AI, there is a growing need for localized compute power,” Farney said.
Inference typically requires low latency and proximity to users, which makes smaller edge facilities more practical.
“We may end up covering the globe with small 1- or 2-megawatt data centers dedicated to  AI  tasks,” he said.
Farney envisions a hybrid future where giant hub data centers and distributed edge facilities coexist to meet the diverse needs of AI workloads.
“This is not a zero-sum game,” he explained. “We will see continued growth in large facilities for batch AI training, and a surge in small data centers for inference and real-time applications.”
The case for data decentralization
Phil Mataras, founder and CEO of AR.IO, a decentralized permanent cloud network provider, said that the current centralized data center approach to storing data 

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In his speech, he highlighted the dual nature of technological advances such as AI which offer both great potential and considerable risks.

“Education is an essential component for everyone to realize their full potential, and for socioeconomic development and prosperity,” said Mr. Guterres.

The promise and risks of AI

The UN Secretary-General stressed that AI and other technological innovations can greatly help students and teachers by providing access to broader information and advanced learning tools.

“But great rewards come with great risks. As AI-driven systems become increasingly powerful, it is easy for human intentions and machine-driven influences to go astray,” he added.

This year, UNESCO, the United Nations educational and cultural agency, dedicated a day to explore the opportunities and challenges of AI

Director-General Audrey Azoulay called for greater investment in teacher and student training so that funds can be used responsibly.

“AI offers major opportunities, provided that its deployment in schools is guided by clear ethical principles. To realize its full potential, this technology must complement the human and social dimensions of learning, not replace them,” said Mr. Azoulay.

Human rights at the heart of AI

This year’s AI Day reminds us that unlocking the potential of AI “depends on putting human agency and human rights at the heart of this rapidly evolving technology,” the UN Secretary-General stressed, calling for guarantees that all users have the right tools and knowledge to “use this technology wisely, safely and ethically.”

UNESCO’s competency framework aims to support learners and teachers in integrating AI into their learning, while the recently adopted Global Digital Compact is expected to help ensure that humans retain control over AI development and governance.

In his closing remarks, Mr. Guterres called for a commitment to “put the humanities at the heart of education systems around the world.”

Divided views onAI

As AI is increasingly integrated into education, countries remain divided over its use. According to the latest data from UNESCO, more than two-thirds of secondary school students in high-income countries are already using generative AI tools to support their learning.

However, education professionals still face significant challenges and a lack of clear guidelines.

In May 2023, a UNESCO survey of 450 educational institutions showed that only 10% of schools and universities had an official framework for the use of AI

Meanwhile, more countries are imposing restrictions on new technologies in the classroom. The latest data from UNESCO shows that nearly 40% of countries now have laws or policies prohibiting the use of mobile phones in schools, a significant increase from 24% in July 2023.

For more insights, listen to Farida Shaheed, the UN Special Rapporteur on the right to education, discuss the role of AI in schools and the challenges it presents in a recent interview with UN News.

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