JUNE 2024

Powering the Future: The
Strategic Role of Data Centresin the AI Evolution in EuropeAUTHOR

Data centre demand is surging, driven primarily by the rapid evolution of AI
technologies. In PIMCO’s view, this represents a significant opportunity forinvestors in European data centres.

Kirill Zavodov
Executive Vice President,
Portfolio Manager

Generative artificial intelligence-driven

Achieving their AI ambitions requires

workloads are rapidly accelerating data

significant investment, which is projected

centre demand, which is likely to boost Tier

to increase by around 44% year-on-year in2 and 3 markets across Europe over the20241. Data centres are central to this AI

next five years. This complements increases

push, serving as the critical infrastructure

in content generation and migration to thethat powers and enables the expansion of AI

cloud in driving secular demand for localisedtechnologies.

data centre capacity globally and, in Europe,
making data centres an increasingly attractive
investment opportunity in our view.

We have already seen a transformational
increase in data centre demand over the last
12 months, with Q1 2024 leasing volumes

In their first-quarter earnings reports forexceeding 1,800 MW (megawatts) globally 22024, the largest technology companies –– just three years ago average quarterly

including Microsoft, Amazon, and Alphabet

leasing volumes stood at 200-300 MW.

– highlighted AI as a primary growth driver,Moreover, forward-looking demand signals

both as a standalone product and as an

are not showing any signs of stabilisation in

additional source of demand for cloudthe near term, as tenants are moving fromservices, which have seen double-digit

contracting individual buildings to (in somegrowth rates.

cases) entire campuses.

1 Source: Morgan Stanley
2 Source: datacenterHawk

2JUNE 2024

THE ROLE OF AI TRAINING AND INFERENCE IN
SHAPING DATA CENTRE TRENDS
There are two primary demands for AI-driven data centre

In essence, just as the logistics sector maintains a dual needcapacity: AI training and AI inference, with the latter expected tofor both expansive big box warehouses to store vast quantities

significantly exceed the former in capacity requirements.

of goods and agile “last mile” logistics to deliver these goods

AI training facilities are used to train generative AI models onlarge datasets, which have grown increasingly complex overthe past five years. For example, OpenAI GPT-2 had around two
billion parameters while OpenAI GPT-4 is estimated to haveapproximately 1.7 trillion.

efficiently to consumers, the AI sector similarly requires robust
training facilities to develop powerful models and extensive
low latency inference capabilities to deploy these models
effectively in real-world applications.
In the context of AI deployments, digital sovereignty isAs these models become more complex, the demand fordata centre capacity rises. Typically, AI training is carried out
in highly dense data centres that are less latency sensitive,
allowing them to be situated in areas with ample land andaccess to low-cost power.

starting to play an increasingly important role. To date, digital
sovereignty has focused primarily on where data is stored
and processed, and with over 70% of European data still being
stored abroad (primarily in the U.S.)3, digital sovereignty isexpected to drive a “near-shoring” of data and be a strong
requirement for more data centre development in Europe.

AI inference facilities are designed to deliver AI capabilities toconsumers, enterprises, and governments, and are therefore
very latency sensitive and are often located in similar places as
cloud data centres.

With generative AI, it is no longer about the location of data
storage and processing but also the type of data that is used
to train the models: many governments and companies
believe that it is important that the models are trained on

Whilst the majority of contracting to date has been focused on
AI training facilities, we expect that the following 18-24 months
will see the build-out of hyperscalers’ AI inference capabilities.

their local norms, customs, and nuances instead of having
one generalised global model. We believe this is likely to be
an additional catalyst for more localised data centre capacity
development over the coming years.

Figure 1: Exponential growth in parameters associated with AI models

Log scale: model size (# of parameters in bn)

10,000NvidiaMicrosoft
MegatronTuring-NLG

1,000

OpenAI GPT-4

1,700

530

OpenAI GPT-3

175

Google PaLM

540100

DeepMind
Chinchilla

Google T51110Microsoft
Turing-NLG

OpenAI GPT-2

17270

OpenAI Dall-E121Feb ‘19

Feb ‘20Feb ‘21Feb ‘22

As of: February 2020 Source: https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/

3 Source: Morgan Stanley

Feb ‘23

JUNE 2024

3THE STRATEGIC MIGRATION TO NEW EUROPEANDATA CENTRE HUBSCAPITALIZING ON AI DEMAND: INVESTMENTOPPORTUNITIES IN EUROPEAN DATA CENTRESThis new growth demand driver for generative AI-driven data

The AI theme is likely to play an important role in investor

centre workloads underscores our continued enthusiasmportfolios over the coming years. Data centres support thisfor the development of data centres in Europe. Yet power

theme without depending on specific winners in the AI racetransmission limitations are increasingly restricting the ability

and enable investors to gain exposure to AI growth without

to expand capacity in the Tier 1 data centre markets (oftentaking idiosyncratic risks. Within the European data centre

referred to as FLAPD – Frankfurt, London, Amsterdam, Paris,

sector, we favour Tier 2 and Tier 3 markets that have theand Dublin) in the near term. These constraints are alreadypotential to benefit from growth in capacity requirements

leading to some hyperscalers strategically shifting workloads

driven by AI and digital sovereignty as well as a continued

out of Tier 1 markets and into Tier 2 and Tier 3 markets

growth in cloud-based demand. The emphasis here is to(such as Madrid, Milan, and Berlin) that may be less power

focus on locations with lower latency and scalable campus

constrained and often have good access to renewable power.

developments that can accommodate increasing AI workloads.

These markets also offer the added benefits of reducing
latency and addressing digital sovereignty considerations of
their end-customers, and therefore are expected to outperform
Tier 1 markets over the secular horizon. Furthermore, andin part driven by the recent push from the European Union
as part of the digital decade strategy, we are seeing strong
support from local governments and municipalities in bringing
data centres to Tier 2 and Tier 3 markets as they see theimportance of supporting critical digital infrastructure, thevalue of the local investment as well as the long-term positivesocial and economic impacts data centres may provide.

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