Data Centre Sector: Riding on structural growth

Introduction 

Data centres are specialised physical facilities that house IT infrastructure such as servers, storage systems and network equipment. They are essential for every online service, from business operations and cloud services to modern artificial intelligence (AI). Businesses require them to handle the large volumes of data generated from their online operations. 

In the global data centre industry, the installed capacity has grown at compound annual growth rate (CAGR) of 14.2 percent between 2019 – 2025, to reach 114.3 GW in 2025. Fuelled by demand from AI and machine learning, the momentum is set to continue.  The installed base is expected to grow to 240.1 GW by 2030, at a CAGR of 16.0%.  In terms of the revenue size, the market is forecasted to grow at CAGR of 11.2 percent from 2025 to 2030, to US$652.0 billion. 

The four main types of data centres are Enterprise, Colocation, Hyperscale and Edge. We will focus on capacity growth, revenue models and capital expenditure trends of Colocation and Hyperscale data centres. 

Singapore-listed companies with significant exposure to data centre assets are the REITs operating the stabilised data centres - include Digital Core REIT (SGX: DCRU), Keppel DC REIT (SGX: AJBU), NTT DC REIT (SGX: NTDU) and Mapletree Industrial Trust (SGX: ME8U).   

In the global data centre industry, the dominant data centre REIT in the U.S. include Digital Realty and Equinix. In Australia, the leading data centre operators are NextDC and Airtrunk.

REIT vs Corporate

Investors can gain exposure to data centres through either REITs or listed corporates, which differ mainly in their revenue model, cash flow profile and risk-return characteristics. 

1. Revenue model:  A data centre REIT receives rental revenue from customers who lease the space to host servers and IT infrastructure. The rental revenue is based on rent per kW, per cabinet or per square foot.  A data centre corporate generates revenue from providing services including cloud computing, managed hosting, connectivity or AI compute.
2. Cash flow visibility: REIT is distribution oriented and defensive. REIT is required by law to distribute a high proportion of taxable income as dividends.  Investors receive a steady and recurring source of income. Corporate, on the other hand, has full discretion over dividends and would typically prefer to reinvest profits into expansion.  Thus, corporate provides higher capital appreciation potential but less income certainty.
3. Risk-return characteristics: REIT offers more predictable returns, driven by long term lease contracts. The tenure of the lease contracts ranges from 5 to 15 years, with built-in escalation clauses. Corporate’s revenue is driven by execution, operational and technological positioning. At the same time, corporate offers significant upside potential in an upcycle.

Industry Growth Trends

The data centre industry grew rapidly in recent years, fuelled by demand from cloud computing and AI.  For the period 2020 to 2025, the industry revenue grew at CAGR 9.1 percent to US$383.8 billion.   Based on the pipeline of data centre under development, the industry is poised to continue with the steady growth.   

The global data centre market is projected to grow at a compound annual growth rate (CAGR) of 11.2 percent from 2025 to 2030, reaching US$652.0 billion.

Key Metrics to evaluating a Data Centre

For investors assessing data centre assets, several operating metrics are critical in determining the attractiveness and performance of the properties. These include vacancy rate, rental rate trend, power usage effectiveness (PUE) and IT load capacity. We will discuss these further on page 22.

1. IT load capacity measure the maximum amount of electrical power that a data centre can supply to IT equipment, expressed through the Density metric. Rack Density refers to the amount of power a fully populated server rack consumes.
2. Vacancy rate and rental rate are key operating metrics of data centres. Vacancy rate is the percentage of commissioned power that is currently available to be leased.
3. Rental rate refers to the monthly cost per kilowatt ($/kW/month) that data centre operators charge tenants for colocation and power.  A higher occupancy rate and rental rates translate to stronger revenue.
4. PUE measures the ratio of the total power consumption of data centre to the energy solely used by IT equipment.  The closer the ratio is to 1.0, the more efficient the data centre.

Investment risks

Power supply risk: A reliable source of power supply is imperative to a data centre.  Power is also the largest cost component. Any interruption, including grid failure, can create immediate revenue loss and customer defection.

Regulatory and environmental risk: Governments are classifying data centres as critical infrastructure requiring interventions. There are energy efficiency directives that include mandatory PUE reporting and sustainability disclosures.

Interest rate and leverage risk: Data centre developers and operators are highly leveraged to the capital-intensive business model. With rises in interest rates, the annual debt service costs increases as well.

Cybersecurity and data breach risk: Data centres are prime targets for cyber-attacks. Ransomware attacks on facility management systems can shut down entire operations. This can lead to reputational damage and loss of business as tenants switch to more reliable providers.

Oversupply risk: There is the possibility that the primary growth drivers like AI and cloud computing do not sustain and that the demand may not meet the future supply. As excessive capacity is being built in many regions, this may lead to potential declines in occupancy rates.

Introduction to Data Centre Sector

Data Centre Sector: A Defensive Asset Class With Strong Growth

Data Centre: An essential infrastructure driving digital transformation

Data centres are specialised physical facilities that house IT infrastructure such as servers, storage systems and network equipment. They are essential for every online service, from business operations and cloud services to modern AI. Businesses require them to handle the large volumes of data generated from their online operations. 

Colocation

Colocation or multi-tenant data centres are third-party facilities renting data centre space, power and cooling to businesses that wish to host their servers and computing hardware offsite. These facilities provide proper components for a functioning data centre. Companies that do not have the space for their own enterprise data centre, or an IT team to manage, would opt for a colocation data centre. As an organisation’s needs change, they can quickly scale up or down.

A key attraction is location, as they are often located near internet exchange points, providing high-speed and low-latency connectivity. It offers tenants scalability and flexibility when adjusting their capacity according to demand. Tenants typically commit to a lease period of three to five years. Tenants have access to the physical space, power, and security to host their critical applications and workloads in an integrated ecosystem. 

For investors, the appeal of the colocation data centre lies in its cashflow visibility. The monthly billing generates monthly recurring revenue for the data centre operator, providing predictable cash flow. In addition, the asset is highly diversified across multiple tenants and requires lower capital investment per revenue dollar compared to hyperscale data centre. As businesses increasingly rely on both on-premise and servers and cloud services, along with backup systems for disaster recovery, demand for colocation data centre space is set to grow. The global colocation market is projected to grow at a 16% CAGR from 2025 to 2030.

Hyperscale

Hyperscale data centres are large facilities owned or leased by major cloud providers.  Hyperscale data centres are typically around 10,000 square feet or larger. They are designed to support very large-scale IT infrastructure. The number of large data centres operated by hyperscale companies reached over 1,000 at the end 1Q2025 and they account for 44% of the worldwide capacity of all data centres. Companies which use them include Amazon, Meta, Microsoft, and Google.

Amazon, Microsoft Azure and Google Cloud are three dominant cloud computing providers. They account for 65% of global cloud infrastructure spending.

As enterprises continue migrating from on-premises infrastructure to online cloud models, the surge in cloud services has resulted in steady demand for hyperscale data centres designed to handle large-scale workloads and provide reliable, high-capacity connectivity.

The global hyperscale data centres is projected to grow from US$162.8 billion in 2024 to US$608.5 billion by 2030 — implying a robust 24.6% CAGR over that period.

Enterprise 

Enterprise data centres are privately-owned facilities that a company builds and operates for its own exclusive use.  All the servers, networking, storage and IT equipment.

They remain relevant for companies that require dedicated infrastructure to meet compliance, regulatory, security requirements, or legacy application constraints.  Enterprise data centres also provide low-latency connections to on-site operations, example factories. 

Typically owned by large companies including banks and financial institutions, telcos, industrial conglomerates with legacy setups, healthcare groups and government agencies. 

As capacity is sized for peak workloads, the facilities operate at low utilisation.  That said, enterprise data centres grow more slowly, usually only when the company itself needs more capacity. The enterprise data centre is projected to grow from US$1.26 billion in 2024 to US$4.73 billion by 2030, representing 24.7% CAGR over 2025 to 2030.

Edge 

Edge data centers are smaller, decentralized facilities located closer to where the data is actually being generated and consumed.

The idea is to process data near the "edge" of the network — the point where end users, devices, or sensors connect – reducing latency from 50-100 milliseconds down to single digits.  They support applications that require near-instantaneous processing, such as 5G, augmented reality, IoT devices, autonomous vehicles, real-time analytics, and content delivery or streaming services.

By processing data closer to the source, edge data centers reduce network congestion and improve performance, making them critical for use cases where speed and responsiveness directly impact outcomes.

Type of operating models

Data centres are usually developed and operated under the following operating models – self-build, powered shell, fully fitted data centres and colocation.

Self-build

Hyperscalers like AWS, Microsoft, and Google are increasingly building and operating their own data centre facilities rather than leasing space from colocation providers. 

In this model, developers are instrumental in sourcing land, managing shell construction, and arranging essential utilities. Developers commonly benefit from early-stage revenue opportunities, such as premiums on land acquisition and profits from initial design-build projects. 

Additionally, hyperscalers often commit to large-scale, multi-phase developments for future expansion, providing developers with a clear and predictable project pipeline.

Developers with expertise in land assembly, permitting, and large-scale shell delivery are best positioned to thrive in this environment.  

Colocation

Colocation facilities are owned and operated by a provider who leases space, power, and cooling to multiple tenants, each housing their own IT equipment. 

This model creates diversified income from many tenants, reducing dependence on any single tenant and often delivering higher internal rates of return (IRRs) than other data centre models. 

However, it requires the owner to manage complex operations like power, cooling, maintenance, and tenant relations, demanding specialized industry knowledge. There are also substantial capital investments and ongoing operational expenses involved in running these facilities. Colocation data centres tend to be more management intensive, and the owner is exposed to operational risks including the maintenance and replacement of M&E infrastructure.

Shell & core or powered shell 

The powered shell model involves the owner delivering a partially finished data centre building that includes the building shell, basic utilities, and power infrastructure, while tenants take responsibility for interior fit-out and IT operations. 

The landlord is only responsible for the provision of power to the property, and the exposure to technical and operational risks is limited. These properties are typically let to a single data centre operator and leases tend to be relatively long, at least 10 years.

This model enables faster development and lower upfront costs compared to colocation facilities, as tenants complete the specialized interior setups themselves. Lease terms are often structured by square meter, similar to traditional real estate leases, offering reduced operational complexity for the owner. 

This model offers a middle ground between full owner-operated colocation centres (higher revenue but complex operations) and hyperscale facilities (one-time development revenue) by balancing upfront investment, flexibility, and operational roles.

Fully-fitted data centres

Landlords handle the full fit-out of these facilities, including the mechanical and electrical (M&E) systems inside the data halls. 

Fully fitted data centres are usually leased to a single tenant on long-term agreements. 

These leases are often structured on a triple-net basis (NNN), so the tenant manages the upkeep of both the building and the installed M&E systems. 

While fully fitted centres carry minimal operational risk, they do come with higher exposure to M&E obsolescence compared with shell-and-core facilities. 

Type of pricing models

Different pricing models of colocation data centre contracts cater to different operational priorities, whether a customer need guaranteed power, lower costs, or room to scale.

• Gross pricing like per contracted kW address high-power demands with reserved allocations, whereas consumption-based billing supports businesses with fluctuating needs.
• Per-kW or pass-through pricing are suitable for companies who want tighter cost control and transparency.
• Triple Net (NNN) leases are common as well, passing operational costs such as maintenance and utilities to tenants.
• Per-rack or bundled pricing are suitable for customers who prefer straightforward, predictable bill. 

From an investor's perspective, the triple-net lease with its stable and predictable margins, is the most preferred. 

The contracts are repriced when the leases expire.  Hyperscalers tend to sign longer leases of between 10 to 15 years. Colocation customers usually commit for a shorter contract period of 1 to 5 years. 

For example, in January 2026, Digital Core REIT signed a 10-year agreement with a global cloud service provider to occupy the facility at 8217 Linton Hall Road. On the other hand, Keppel DC REIT’s portfolio of colocation contract has a weighted average lease expiry (WALE) of 3.2 years as at 31 December 2025. 

Demand drivers of Data Centres

While cloud computing, data generation and storage are long-term demand drivers for data centres, artificial intelligence and machine learning   are powerful catalysts since 2022. The trend is set to continue, supported by several structural factors.

#1 – Rising demand for cloud computing 

Cloud computing is the biggest data centre demand driver. Enterprises are still shifting workloads from on-premise systems to public and hybrid cloud. This migration creates sustained demand for both colocation and hyperscale capacity.

As more organizations move workloads to the public cloud for scalability and convenience, hyperscalers will continue to expand across markets. The structural demand drivers continue to fuel growth in the data‑centre industry, attracting significant capital. 

Hyperscalers are securing new development projects, creating additional cloud regions, and upgrading digital infrastructure to serve clients and meet rising demand.

The big three cloud providers—Amazon Web Services, Microsoft Azure, and Google Cloud—keep expanding their offerings, adding more edge and core services. This strengthens their role as the go-to platforms for large enterprises and government agencies. 

Public cloud providers drive most of the world’s data centre leasing, in both self-build and colocation capacity. They accounted for 40% of leasing transactions in 2024 and roughly 36% of total leasing activity to date.

Combined cloud revenues for the four major US cloud providers — Microsoft, Amazon Web Services, Google, and Oracle — grew 16% in 2024 and have expanded at a 23% CAGR over the past four years. 

The global cloud computing market size is estimated to reach US$2,390 billion by 2030, registering to grow at a CAGR 20.4% from 2025 to 2030. 

Notably, major tech giants like Alphabet, Amazon, Meta, and Microsoft more than tripled their capital expenditures from around US$93 billion in 2020 to approximately US$362 billion in 2025. 

#2 – Artificial intelligence models 

AI has also become a key driver in data centre demand worldwide. The increase in capital expenditure is also mainly AI-driven, with heavy investment in data centres, high-performance GPU infrastructure, and cloud capabilities to support the next wave of AI innovation.

AI-specific infrastructure is growing rapidly. In the US, OpenAI’s $500 billion “Stargate” project aims to build next-generation AI facilities nationwide. Japan plans to fund domestic AI chips and edge infrastructure to reduce reliance on foreign technology. In the UK, government involvement in data centre planning shows a commitment to boosting AI capabilities and research infrastructure. 

Generative AI, including tools for creating images, videos, text, and chat, is being widely adopted by major companies worldwide. Models like OpenAI’s DALL-E and ChatGPT are key drivers of this AI revolution.

As AI models become larger and more powerful, they require more data centre capacity. Generative AI is driving significant growth in the global data centre market. 

AI workloads, particularly generative AI, are projected to account for approximately 40% of total data centre demand through 2030. AI workloads consume vastly more electricity than traditional computing, as they require fundamentally different hardware configurations with exponentially higher power consumption.  The computational intensity of AI model training is staggering as training GPT-4 alone required around 30 megawatts of power. 

Cloud and AI revenues are expected to grow at a 23.3% CAGR from 2024 to 2028, up from 16.4% from 2020 to 2024, with AI-related revenue alone projected to grow 72.5% annually over the same period.

#3 – Meeting regulatory requirements

As data centre markets mature, regulations tend to tighten. Established markets worldwide face measures such as temporary halts on new projects, stricter sustainability requirements, limits on noise and environmental impact, and restrictions on suitable locations for building data centres. Stringent regulations in established market could persuade companies to explore emerging markets.

Many countries now require certain types of data to remain within national borders. This drives demand for local data centres:

• Local storage mandates: sensitive data (financial, healthcare, government) must be stored domestically.
• Edge computing deployment: closer proximity to users is required to reduce latency while complying with local data laws.
• National security considerations: governments prefer domestic infrastructure to protect critical data from foreign access.

In Europe, growth in data centre market was partly to support compliance with data‑sovereignty regulations such as General Data Protection Regulation (GDPR). 

Demand, as represented by absorption, refers to the newly leased capacity  each year, as measured in MW.  North America has the highest demand for data centre, at 6,793 MW in 2024. Absorption refers to the new leases recorded and is a reflection of the demand for data centre capacity. As demand has outpaced new supply, vacancy rates have been declining since 2020. Among the regions, North America has seen particularly strong growth in data centre absorption.

#4 – 5G adoption

With rising 5G deployment, data centres are crucial for telecommunications infrastructure, processing calls, messages, and data for mobile and internet services. With 5G, edge data centres help bring computing resources closer to users for lower latency.

Example telecommunications or 5G networking companies include Verizon, AT&T, China Mobile, Comcast, and Vodafone.

#5 – Others

• Website, application and content hosting: Data centres host websites, applications, and mobile apps, ensuring they are available to users with high reliability, speed, and scalability. As of December 2024, approximately 33.0% of all websites are hosted on servers located in the United States. In addition, data centres power content delivery networks that cache and distribute media, enabling fast, high-quality streaming for videos, games, and other content. The rise of platforms like Netflix has pushed global internet traffic higher, driving additional demand for data centre capacity.
• Enterprise Resource Planning (ERP) and business applications: Data centres host ERP systems and business applications like finance and supply chain management. Users include SAP, Oracle and Workday.
• Data storage, backup and analytics: Data centres hold large volumes of information, supporting backup and disaster-recovery needs. This helps organizations maintain data integrity and meet regulatory requirements.  Data centres power analytics platforms that process and analyse large datasets in fields like finance and healthcare, providing insights for data-driven decision-making. Example big data and analytics companies include Databricks, Snowflake and Palantir.

Key Data Centre Evaluation Metrics  

Vacancy, rents, PUE, and IT load capacity are key metrics

For investors assessing data centre assets, several operating metrics are critical in determining the attractiveness and performance of the properties. These include vacancy rate, rental rate trend, power usage effectiveness (PUE) and IT load capacity.

For the REIT, they are asset owners and are likely to focus on vacancy rate and rental growth.  For the operators, they may not own the assets and are focus on growth. As operators are providing a service, they do not have the avenue to pass on the operating expenses.  They focus on PUE and rack density in order to optimise the profitability.  

Vacancy Rate

Vacancy rate and rental rate are key operating metrics of data centres.  Vacancy rate is the percentage of commissioned power that is currently available to be leased.

Vacancy rates are extremely tight. About 20 markets across the world have extremely tight capacity, with vacancy below 5%. Several markets reported vacancy rates below 1%. 

Singapore remains one of the tightest markets globally. In late 2024, Singapore had only 7.2 MW of available capacity with a vacancy rate of about 1%, and by 1Q25, this had edged up only slightly to about 2% The market's overall vacancy rate stays tight at around 2%, with operators awaiting government approval of an additional 300 MW of capacity.

Rental Rate and Rental Growth

Rental rate refers to the monthly cost per kilowatt ($/kW/month) that data centre operators charge tenants for colocation and power.  A higher occupancy rate and rental rates translate to stronger revenue.

To offset inflation, the agreements with tenants have contracted rental escalations per annum during the relevant lease periods. 

Pricing trends have generally been on a uptrend and expected to grow in the medium term. Hyperscale prices are expected to rise by 15.2% in the Americas, 6.7% in APAC and 16.9% in EMEA between 2024 and 2027F. Wholesale prices are similarly expected to rise across all three regions, with increases of 18.8% in the Americas, 6.7% in APAC and 13.0% in EMEA between 2024 and 2027F.

Power usage effectiveness (PUE)

PUE (Power Usage Effectiveness) is a key metric used to measure the energy efficiency of a data centre.

PUE measures the ratio of the total power consumption of data centre to the energy solely used by its IT equipment.  The closer the ratio is to 1.0, the more efficient the data centre. 

Launched in May 2024, the Singapore government’s Green Data Centre Roadmap targets for all Singapore data centres to achieve a PUE below 1.3 at 100% IT load in the next 10 years. According to Uptime Institute, the average PUE across global data centres is around 1.55. In Singapore, our facilities’ PUE ranges from 1.2 to 1.9, with an average of around 1.47. Newly built data centres, however, achieve a PUE of about 1.35.

IT load capacity and rack density

IT load capacity measure the maximum amount of electrical power that a data centre can supply to IT equipment, expressed through the Density metric. 

Power density refers to the amount of electrical power supplied to a specific area within the data centre, usually measured in kilowatts per square foot (kW/sq ft) or kilowatts per rack (kW/rack). 

Rack density refers to the physical concentration of servers, storage, and networking equipment within a rack, typically measured as the number of units (U) of equipment installed per rack.

Rack density determines the physical space utilization in the data centre. It impacts cooling and airflow design, as densely packed racks generate more heat. 

Rack density has been climbing steadily, and that shift matters for valuation. In 2010, most data centres ran at 4–5 kW per rack. By 2020, densities had doubled to 8–10 kW. New completions today average 12–15 kW, and operators are still chasing demand as customers push peak loads toward 16–20 kW.

What this really means is that facilities built for higher densities can command better economics. They support more compute per square foot, attract AI-heavy workloads, and justify higher pricing because the power and cooling backbone is tougher to replicate. 

In hyperscale environments above 10 MW, roughly half of operators already use racks above 20 kW, and close to one in five run beyond 40 kW. AI applications, particularly those involving large language models (LLMs) and deep learning (DL), need significantly more computational power. This has led to the development of high-density racks that can support 60-120 kW or more per rack.

Learn more about data centre sector by downloading our guide for investors here. 

For investors who want to understand the broader AI opportunity, you can read our guide on how to invest in AI, where we look at the different parts of the AI value chain beyond just the big US technology stocks. 

You can also read our take on whether the AI rally has gone too far, where we discuss the reasons the rally may be real, as well as the warning signs investors should watch.

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