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Opinion

Why proactive asset management is mission-critical for APAC datacentres

The Asia-Pacific region is leading a global datacentre expansion, but surging energy demands and the risk of outages will require datacentre operators to adopt proactive strategies to ensure a resilient and sustainable digital future

By
  • Pankaj Sharma
Published: 10 Jul 2025

The Asia-Pacific region is rapidly emerging as a global leader in datacentre expansion, driven by the increasing adoption of artificial intelligence (AI), digital transformation, and cloud infrastructure investment. Markets such as Indonesia, Malaysia, the Philippines, Singapore, Thailand, Vietnam and China are rapidly evolving into key datacentre hubs. This surge is underpinned by the region’s fast-paced digitalisation, a growing internet user base, and supportive government policies.  
 
According to IDC, APAC’s installed datacentre power capacity is expected to grow at a compound annual rate of 14.2%, reaching 94.4 gigawatts by 2028. While this growth signals the region’s critical role in the global digital economy, it also raises complex challenges – ensuring infrastructure resilience, managing surging energy demand, and curbing carbon emissions.

As the backbone of digital infrastructure, datacentres must deliver uncompromising resilience, energy efficiency, and continuous uptime, particularly as AI-driven workloads intensify. In critical sectors such as healthcare, financial services, logistics, and emergency response services, even a brief outage can jeopardise lives, undermine business continuity, and erode public trust.  

This is where proactive electrical asset management becomes a strategic imperative.

Taking stock of your assets

The first step towards maximising uptime in AI-driven datacentres is a thorough assessment of infrastructure, from electrical systems to mechanical equipment. Evaluating asset performance, condition, and efficiency helps identify vulnerabilities that could disrupt operations. A proactive strategy anticipates issues before they arise, aligning maintenance with AI workloads to minimise downtime and performance degradation. As AI demands grow, scaling infrastructure efficiently while integrating renewable energy sources ensures both operational resilience and supports long-term performance goals.

Electrical failures remain a leading cause of unplanned downtime in mission-critical environments. Yet, traditional calendar-based maintenance approaches often fail to detect underlying issues in time. This underscores the need for predictive, data-driven assessments that detect early signs of failure – like insulation degradation, temperature anomalies, or loose connections – before they result in critical interruptions.

The partnership between Schneider Electric and Compass Datacenters demonstrates these benefits in action. By utilising services like EcoCare – a condition-based maintenance membership services plan – they’ve shifted from calendar-based servicing to real-time asset tracking, reducing intrusive on-site maintenance by 40%. This transition leads to operational improvements, including cost savings and a reduction in downtime, while also addressing workforce shortages. While these strategies have contributed to improvements in operational efficiency, the primary benefit lies in minimising human intervention, which reduces the risk of outages and enhances overall datacentre reliability.

Meeting the growing demands of AI

Maximising uptime is just the beginning – embracing a proactive asset management approach unlocks a range of benefits that sustainability and enhance efficiency, resilience, and future readiness. By leveraging predictive analytics, digital twin technology, and AI-driven insights, datacentres can optimise operations while reducing costs and risks.   

  • Increased energy and operational efficiency – digital predictive analytics and digital twin technology shift maintenance from reactive to proactive, reducing total operational expenses and minimising unplanned downtime. This shift can improve resource allocation by 20%, ensuring datacentres operate at peak efficiency while lowering overall maintenance costs. Advanced energy analytics and intelligent automation help optimise power usage, reduce e-waste, and extend asset lifespan. Machine learning refines operational strategies, improving energy efficiency and supports effective tracking of key performance indicators.
  • Resilience and future-readiness – Connected Service Hubs (CSH) and remote diagnostics reduce on-site maintenance, addressing issues such as outages, which 66% of datacentre operators attribute to human error. Integrating remote monitoring, digital asset management, and AI-driven insights from the design stage ensures seamless sensor integration and long-term efficiency. Digitally connected assets enable data visibility, allowing for better performance tracking and optimisation across the asset’s lifecycle. Predictive asset management reduces the need for manual inspections and enables early failure detection, allowing technicians to focus on high-value tasks. This self-learning framework not only enhances reliability but also improves safety by minimising exposure to live electrical equipment, allowing operators to mitigate risks during technology transitions, and ultimately strengthen datacentre resilience in an evolving energy landscape.

Energy efficiency as the new industry standard

The global datacentre boom is fuelling a sharp rise in electricity demand. In 2024, datacentres consumed around 460 TWh of power worldwide – a figure expected to nearly double to 945 TWh by 2030. In fast-growing regions like Asia-Pacific, this trajectory makes one thing clear: energy efficiency is no longer optional – it’s an absolute necessity.

This urgency is amplified by the crucial role datacentres now play in the digital economy – supporting everything from financial services and healthcare to smart cities, entertainment, and research. At the same time, regulators, investors, and communities are increasing pressure to reduce their environmental footprint. Operational efficiency must evolve from a business goal into an environmental responsibility. The pressure to deliver sustainable uptime is mounting – and the path forward lies in proactive asset management.

Fortunately, the tools to drive change are already here. Intelligent automation, AI-powered systems, and software-defined infrastructure are enabling datacentres to reduce e-waste, optimise energy use, and actively track sustainability metrics across the asset lifecycle. These innovations create a self-reinforcing loop of smarter, greener operations – powering not just digital transformation, but a more sustainable digital future. 

Pankaj Sharma is executive vice-president for secure power, datacentres and global services business at Schneider Electric 

Read more on Datacentre energy efficiency and green IT