What AI’s ‘Sputnik moment’ means for data centres

Andrew Parsons | Resolution Capital

AI-related stocks sold off heavily on 27th January 2025 as news emerged about DeepSeek R1, a Chinese developed AI large language model (LLM). DeepSeek has asserted it can deliver performance comparable to U.S. developed AI models, such as ChatGPT, but at a fraction of the cost and with much less physical computing power required.

While there is some healthy scepticism towards certain aspects surrounding DeepSeek, advancement in its algorithm has been widely recognised by the tech community including the leaders of NVIDIA, OpenAI and Meta.

DeepSeek’s open-source program allows it to be quickly studied and adopted globally, and therefore, it could represent a step-change in resource intensity required for the continued development of AI. This has led investors to re-assess the bullish trajectory of demand for advanced computer chips (GPUs), physical infrastructure and power required for the build-out and training of AI models.

As a result, stocks ranging from chip manufacturers, utilities, data centre equipment manufacturers and data centre landlords experienced significant share price declines following the DeepSeek news.

Given our overweight position and broader interest in data centres, we provide here an outline of our current thoughts on the potential implications for the data centre real estate sector, with the caveat that there are still a lot of unknowns.

Potential negatives:

• AI-related demand for data centres may not live up to previous bullish expectations as future AI model developments could become more resource efficient, requiring fewer advanced chips, less power and cooling, and less data centre capacity than previously anticipated.
• The potential reduction in demand could eventually lead to oversupply conditions in data centres - although this is not anticipated in the near-term given significant supply bottlenecks and lengthy lead times for electricity grid upgrades, electrical transformers and air-conditioning components required to satisfy current demand levels.
• Big tech companies could reduce capex on data centre build outs. While previously announced capex might continue in the short term, it may be re-oriented towards software development rather than hardware (AI training infrastructure). Nevertheless, on its earnings call on 29th January, Meta re-iterated its plans to increase total capex spending to US$60-$65 billion this year – including increased investment in generative AI.
• Investor enthusiasm for AI-related stocks (GPU’s, data centres, utilities etc) since AI emerged as a significant demand driver two years ago, has pushed valuation multiples to elevated levels relative to other sectors.

Potential positives:

• DeepSeek may have over-stated its efficiency, and as such, it may not prove to be as great a departure from current AI infrastructure needs as initially feared. DeepSeek’s capabilities benefited from US developed large language models, which muddies the claim that DeepSeek R1 was trained for <US$6 million. If R1 had to be trained from scratch, the cost would have been significantly higher.
• There is a long history of technology efficiencies driving increased adoption and ultimately growing the total demand pool. Microsoft's CEO was quick to reference Jevons Paradox, the observation that improvements in resource efficiency often leads to increased, rather than decreased, overall consumption of that resource.
• The emergence of cheaper and more efficient AI models could potentially spawn new entrants (previously precluded due to the significant upfront costs, sometimes referred to as the ‘money moat’ that benefited incumbent big-tech companies).
• Cheaper AI development could speed up AI adoption. Greater adoption could drive greater AI inference demand, benefiting existing data centre owners located in major population centers, as they cater to end users requiring strong network connectivity and lower latency.
• While DeepSeek is more efficient and its advancements are likely to be widely adopted, major tech companies remain focused on developing more sophisticated artificial general intelligence (AGI), which will likely still require increased computing power for both training and inference.
• National security concerns and geopolitics could drive duplication of AI investment. DeepSeek's emergence may compel tech companies and governments globally to increase capex to further improve AI capabilities.

Location, location, location

Our conviction in data centres is predicated on the expansion of the digital economy across a broad range of use cases, not just AI. Admittedly, AI has attracted disproportionate attention in recent years thanks to the potential impact it could have on the economy and society.

The data centre industry is presently supply constrained for a multitude of reasons mentioned herein. No doubt those with current capacity are enjoying pricing power and the question now is how long this will last if the more immediate demand side has been dampened.

We also acknowledge that many players are trying to get entitlements (real estate planning and power) to bring on material supply in future years. Our exposures are focused on superior in place platforms that provide space to a multitude of users for a variety of IT use cases, located in major metropolitan areas where there is deep tenant demand and dense fibre connectivity.

This is in contrast to some of the more recent wave of proposed AI training data centres that are mostly being developed by private capital and, by necessity, are often located in more remote locations where there is available land, cheap power, and typically oriented to a single tenant user.

If there were a reduction in AI training demand, we believe the more remote data centres would be more negatively impacted.

Data centre rent hikes not just about AI

As illustrated in the following chart, wholesale data centre rents inflected positively in 2022, after a decade of declining rents. Context is important here as it is important to note that rents declined during that period despite solid demand from broader digitalisation trends including the shift to cloud computing.

The rental decline can mostly be attributed to conditions that were conducive to profitable data centre development including benign construction cost inflation, declining interest rates and, tangentially, declining real estate cap rates. Despite a competitive rental market, these conditions allowed data centre developers to maintain healthy profit margins even as rents were falling.

Wholesale data centre rents inflected positively in 2022 as most of these conditions reversed (construction cost inflation spiked, interest rates rose dramatically and real estate cap rates increased), coinciding with the emergence of large-scale AI as an additional demand driver, together with significant supply bottlenecks in securing power to data centre sites and lengthy lead times for certain building components including electrical transformers and air conditioning equipment.

Importantly, it was a confluence of factors that drove the inflection, not only the emergence of AI demand.

You can see the full version of Resolution Capital’s research note “AI’s Sputnik Moment” here.

First published on the Firstlinks Newsletter. A free subscription for nabtrade clients is available here.

All prices and analysis at 5 February 2025.  This document was originally published on firstlinks.com.au on 5 February has been prepared by Resolution Capital (ABN 50 108 584 167, AFSL 274491) an affiliate manager of Pinnacle Investment Management. The content is distributed by WealthHub Securities Limited (WSL) (ABN 83 089 718 249)(AFSL No. 230704). WSL is a Market Participant under the ASIC Market Integrity Rules and a wholly owned subsidiary of National Australia Bank Limited (ABN 12 004 044 937)(AFSL No. 230686) (NAB). NAB doesn’t guarantee its subsidiaries’ obligations or performance, or the products or services its subsidiaries offer.  This material is intended to provide general advice only. It has been prepared without having regard to or taking into account any particular investor’s objectives, financial situation and/or needs. All investors should therefore consider the appropriateness of the advice, in light of their own objectives, financial situation and/or needs, before acting on the advice.  Past performance is not a reliable indicator of future performance.  Any comments, suggestions or views presented do not reflect the views of WSL and/or NAB.  Subject to any terms implied by law and which cannot be excluded, neither WSL nor NAB shall be liable for any errors, omissions, defects or misrepresentations in the information or general advice including any third party sourced data (including by reasons of negligence, negligent misstatement or otherwise) or for any loss or damage (whether direct or indirect) suffered by persons who use or rely on the general advice or information. If any law prohibits the exclusion of such liability, WSL and NAB limit its liability to the re-supply of the information, provided that such limitation is permitted by law and is fair and reasonable. For more information, please click here.