Data Centre Capacity Constraints Slow Microsoft Azure Growth

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Satya Nadella notes AI services are on track to surpass an annual run-rate of US$10bn next quarter
Nuclear power deal and global expansion plans show Microsoft is eager to meet AI computing demands, but tech giant warns of AI and cloud revenue slowdown

Microsoft, the global technology company behind Windows and Azure cloud services, has reported first-quarter revenue growth of 16% to US$65.6bn, driven by increasing demand for AI services.

The company's Azure cloud computing division, which provides on-demand computing resources through data centres, saw revenue rise 22% to US$38.9bn compared to the previous year. Azure is part of Microsoft's Intelligent Cloud segment, which includes enterprise services, server products, and cloud services.

"We are expanding our opportunity and winning new customers as we help them apply our AI platforms and tools to drive new growth and operating leverage," says Satya Nadella, Microsoft's chairman and CEO, who has led the company's transformation into a cloud computing powerhouse since taking the helm in 2014.

Microsoft's AI business is booming, yet capacity constraints linger

Investing in AI and cloud infrastructure

To support the computational requirements of AI workloads - which require significantly more processing power than traditional cloud computing - Microsoft has committed to expanding its global data centre footprint. The company plans to increase capacity by 1.5 gigawatts (GW) by July 2025, representing a tripling of its current infrastructure.

This expansion comes as demand for generative AI services, which can create text, images, and code based on user prompts, continues to grow. Microsoft's partnership with OpenAI has also driven adoption of these services across its cloud platform.

Key facts
  • Recent infrastructure commitments from Microsoft include a US$2.9bn investment in Japan and US$3.16bn in the UK, where plans include converting the former Eggborough power station site in North Yorkshire into a data centre campus.

These investments form part of Microsoft's strategy to maintain competitiveness with cloud rivals Amazon Web Services (AWS) and Google Cloud.

Likewise, Microsoft’s Japanese investment will focus on expanding data centre capacity to support AI services and enhance the country's digital infrastructure. In the UK, the investment includes both data centre construction and AI skills training programmes.

Confronting compute demands

The company's AI business is performing strongly, with Satya Nadella noting that AI services are on track to surpass an annual run-rate of US$10bn next quarter, which will make it the fastest growing business in our history to reach this milestone.

The computing demands of AI have led Microsoft to secure long-term power agreements, including a 20-year contract to purchase the entire output from a reactor at Three Mile Island nuclear power station in Pennsylvania. This move reflects the growing importance of securing reliable sustainable power sources for data centre operations.

Azure's customer base has expanded by 80% year-on-year to 39,000 users. The platform now operates AI-capable data centres across more than 60 global regions, while usage of its Azure-powered OpenAI service has doubled in six months.

"AI-driven transformation is changing work, work artefacts, and workflow across every role, function, and business process," Satya Nadella said in a first-quarter earning press release.

Capacity constraints, yet Nadella remains confident in AI strategy

Despite these investments, Microsoft has warned of slower quarterly cloud revenue growth due to infrastructure limitations. 

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This capacity shortfall highlights the challenges faced by cloud providers in meeting the rapid growth in demand for AI services. Data centre construction typically requires significant lead time for planning, permitting, and construction, making it difficult to respond quickly to sudden increases in demand.

Data centre operators around the world are currently facing issues with power availability, supply chain constraints and the need to balance rapid growth with sustainability. 

Such challenges have implications for the entire data centre sector, suggesting that infrastructure development timelines may need to be accelerated to meet the computing demands of next-generation AI applications.


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