Data Centres: The modern-day shovels in the AI (Artificial Intelligence) gold rush

The mass adoption of generative Artificial Intelligence (AI) (a type of AI that is capable of creating new data or content, rather than simply analysing or processing existing data), marked by the run-away success of ChatGPT since November 2022, has sparked interest akin to the Californian Gold Rush.

Investment markets have jumped back on the innovation bandwagon, rewarding pioneering firms like Nvidia, Google and Microsoft, that have gained competitive advantages through research and development efforts. With mega-cap tech enjoying higher share prices as a consequence, investors are understandably now looking for the next group of beneficiaries, whilst seeking to avoid high-risk or even loss-making companies.

Here, Ben Forster a fund manager on the real estate team at Schroders, and co-manager of the Schroder Digital Infrastructure fund, tells us more about data centres – the modern day shovels in the AI gold rush

When NVidia released its first quarter results, it marked a watershed moment for the AI supply chain, highlighting the incredible recent demand growth for its hardware. In explaining its more optimistic sales outlook, the company mentioned ‘data centres’ no less than 56 times during the results call for investors on 24 May 2023. It is clear that its advanced graphics processing units (GPUs) entirely depend upon high-performance, secure and stable data centre environments. We believe that these critical infrastructure assets are the ‘pick-and-shovel’ play for the AI goldrush.

The evolution and of data centres from communications exchanges into AI launchpads

Data centres have evolved dramatically from their origin as telecommunications hubs for hosting the internet in the late 90’s and early 2000’s. Technological and policy advancements have since driven their transformation into larger, more localised, more resilient facilities, boasting state-of-the-art cooling systems, redundant power supplies and advanced security measures.

Over the past two decades, data centres were in many cases spun out of telecommunications companies into infrastructure businesses more suited to their long term ownership. These buildings both host the public internet and also enable businesses to privately connect to their end customers and partners. Coupled with the smartphone revolution which has led to an unprecedented surge in data generation, the demand for data storage and processing capacity continued to soar.

AI data science has been around since the 1950’s, but with the affordable and widespread availability of advanced AI technology much more recently, adoption has rocketed. This is in no small part due to the cloud computing giants such as Amazon and Microsoft developing their own internal applications and beginning to make these available to businesses of all sizes. In 2021, the world’s leading data centre operators such as Equinix also began to offer ‘AI LaunchPad as-a-service’ to customers within their facilities, in partnership with NVidia.

Translating the growth potential into numbers

The potential size of the opportunity remains subject to fierce debate, but forecasters estimate that total demand for data centres, as defined by power consumption, could hit 35 gigawatts (GW) by 2030 in the US market alone, up from 17 GW in 2022. A GW is a unit of power equal to one billion watts, often used to describe the output of large-scale power plants or other energy systems. The US currently constitutes about 40% of the data centre global market. Industry analysts estimate that the future power consumption related to AI deployments could increase from approximately 1GW in 2023 to 7GW by 2026, representing a $12bn revenue opportunity for data centre operators and 15-20% growth versus existing total data centre capacity.

Equinix: a case study

Equinix is a leading player in the global data centre industry, owning a portfolio of 248 multi-tenant data centres across 32 countries, that host 10,000+ companies, with 450,000+ inter-connections between these customers. In 2023, Equinix identified a $21 billion addressable market for data centres services to support AI by 2026, based on its current operations and capacity. Whilst it will likely only take a percentage share of this opportunity, it could significantly grow its current revenue of around $8 billion per annum (source: company, June 2023).

Equinix’s services have grown beyond offering physical space, power, cooling and connectivity to increasingly focus on network services, growing its competitive advantages. Its Singapore metro alone hosts 300+ network service providers, four internet exchanges and six public clouds, resulting in 25,000 inter-connections. We believe that such dense networks are perfectly placed to deliver the results of AI calculations (known as AI ‘inference’), as they sit at the edge of the network, close to end users.

Can our power grids sustainably keep up with AI computing demand?

Supply was already struggling to keep pace with surging demand for data centre space in major metropolitan areas, prior to the mass adoption of AI tools. Supply chain bottlenecks and a lack of distributable power have led to low vacancy rates and significant pricing power for data centre owners in these locations.

AI software is trained on enormous quantities of data in order to return informative responses. For advanced applications such as these, GPUs are used in place of Central Processing Units (CPUs) given their ability to more efficiently process multiple computations simultaneously. Whilst GPUs are more efficient per byte of data processed, total power consumed is likely to increase as new uses cases are introduced, as suggested in the forecasts above. As data centres begin to host more high power GPUs to support AI, the draw on our electrical grids will only become more acute. Some utility providers are already setting quotas that limit the construction of new facilities, making existing facilities more valuable.

The AI supply chain must work hard to derive more efficiency from existing resources. Innovations around liquid cooling and optical networking technologies are advancements set to reduce the energy consumption needed to run high performance chips. What’s more, data centre operators and occupiers are working intently to add new large scale renewable energy supplies onto the grid.

Equinix’s strong commitment to sustainability and energy efficiency set a benchmark in the data centre industry. The company is closing in on their pledge to use 100% clean and renewable energy across their global platform (currently 96%) and has reduced operational emissions 23% from their 2019 baseline.

Conclusion: AI adds to the unprecedented demand for data centres

Data centres, as the critical infrastructure behind the digital economy, are set to play a key role in delivering new AI tools to consumers and businesses.

As with any new technology, the ultimate size of the AI market opportunity remains open for debate. Data centre operators will need to carefully manage environmental and regulatory concerns. We believe that companies with long track records of innovation should see their revenue growth augmented by this new wave of applications, offering a ‘pick-and-shovel’ play on the AI goldrush.