Enterprises need to future-proof storage infrastructure in the AI era, planning for performance, reliability, and capacity for modern workloads.
Enterprises across Asia Pacific are racing to implement AI. Driven by rapid AI uptake across tech and industry segments like finance, wholesale trade, and manufacturing, Singapore’s digital economy accounted for 18.6 percent of gross domestic product (GDP) in 2025 – up from 14.9 percent in 2019.
The rise of AI has fundamentally changed the game: workloads have become dynamic and data volumes are expanding at unprecedented rates, demanding infrastructure that scales effortlessly to support continuous innovation.
According to Market Data Forecast, the Asia Pacific AI market is projected to grow at nearly 40% compound annual growth rate (CAGR) to $1.365 trillion by 2033. Today, as AI applications continuously learn, retrain, and expand, storage must deliver cost efficiency, adaptability, and uncompromising reliability at massive scale.
To keep pace, we need to look at future-proofing storage – and that means building an infrastructure that can grow with data demands, handle unpredictable workloads, and sustain long-term performance and durability, all while keeping costs and energy use in check.
A truly future-proof storage strategy rests on three pillars: scalable economics, dynamic adaptability, and sustainable operations.
Scalable economics: The HDD foundation
AI’s data demands are enormous and growing rapidly. Managing the explosion of unstructured data, now measured in petabytes, has become one of the biggest challenges facing organisations today. According to IDC, in 2025, more than 86 percent of enterprise data generated will be unstructured, which will grow at a 26.4 percent CAGR over the next five years. Without the right storage strategy, costs can quickly spiral out of control.
To address this, enterprises are turning to strategic and automated tiering, with HDDs serving as the economic backbone. HDDs remain indispensable to hyperscale and cloud data centres, with nearly 80% of data within the cloud still residing on hard drives by 2029, according to IDC. Their economics at scale, reliability, and performance make them the foundation of sustainable data growth. They deliver predictable total cost of ownership (TCO), allowing enterprises to store and analyse vast datasets efficiently without unsustainable capital or operating expenses.
AI is making “cold” data – or data that needs to be stored for long periods of time – valuable again, transforming archives into actionable insights. HDD-based storage provides the scale, reliability, and efficiency required for modern workloads by supporting AI workflows by keeping massive datasets accessible at an economical scale for training and retraining models, while higher-performance flash is reserved for inferencing and metadata operations.
Dynamic adaptability: Storage tiering that scales with your data
In the age of AI, data is constantly in motion, shifting between hot, warm, and cold tiers depending on how and when it’s used. Enterprises need infrastructure that can keep pace with this fluidity. Future-proof storage must support automated tiering, scale-out architectures, and intelligent, software-defined management. These capabilities orchestrate data movement across storage tiers seamlessly, without manual intervention, optimising both cost and performance.
Adaptability also means resilience. Modern HDD-based infrastructures can scale up or scale out to meet surging data demands without costly migration or downtime. Innovations such as energy-assisted magnetic recording (EAMR) and dual-actuator HDD designs further boost performance, offering faster rebuilds, higher throughput, and better energy efficiency to match the real-time demands of AI workloads.
Playing a crucial role as the foundation for data lakes – the central repositories that store and transform massive volumes of structured and unstructured data for AI – HDDs help data flow through every stage of the AI journey, from ingestion to training, retraining, and compliance, ensuring that enterprises remain agile in a rapidly shifting data environment.
Sustainable operations: Building for long-term viability
AI promises to be transformative, but it also brings significant energy costs. Training a single large AI model can consume as much power as hundreds of homes use in a year. According to PwC, electricity demand in Asia Pacific is projected to rise from around 320 TWh in 2024 to 780 TWh by 2030, yet only about 32 percent of this will be met by renewable energy.
Sustainability is no longer a corporate buzzword – it’s a business imperative. In Asia Pacific, governments and enterprises across the region are recognising this reality.
To drive a greener digital future, the Singapore government has also launched a Green Data Centre Roadmap in 2024 to pioneer the sustainable growth of data centres. Most recently, the government has also announced that Jurong Island will be a global testbed for new energies and low-carbon technologies and will host the city’s largest low-carbon Data Centre Park to accommodate 700MW of capacity.
Energy-efficient storage has become a procurement priority. High-capacity HDDs, in particular, allow enterprises to consolidate workloads and reduce overall power consumption per terabyte while maintaining performance and reliability. For example, replacing 24TB with 32TB drives to deploy 2 petabytes of storage can reduce server count by 25 percent, cut energy consumption per terabyte by 20 percent, and lower infrastructure and maintenance costs.
Strategic storage architectures that leverage HDD economics, combined with deduplication and compression, enable organisations to scale AI responsibly while improving operational efficiency and supporting environmental commitments. The result is a storage ecosystem that balances cost, performance, and sustainability – the very definition of future-proof growth.
The future-proof formula
Building future-proof AI storage requires more than just speed. It demands a holistic approach that integrates scalable economics, dynamic adaptability, and sustainable operations. Each pillar reinforces the others: sustainable economics ensures data can grow economically at scale; dynamic adaptability enables storage to respond intelligently to ever-changing AI workloads; and sustainable operations make that growth environmentally and financially viable.
At the heart of this approach are HDDs, which provide the reliability, cost-efficiency, and performance needed to support AI at scale. By combining these elements, enterprises can create a storage architecture that is resilient, responsive, and ready for the long term, forming a foundation capable of supporting both today’s AI initiatives and tomorrow’s innovations. Recognising storage as a strategic enabler positions organisations to unlock AI’s full potential without being overburdened by its operational demands. The time to build this future-proof foundation is now.
References
- IMDA, Singapore’s Digital Economy at 18.6% of GDP, up from 14.9% in 2019; Growth fuelled by accelerating digitalisation and AI adoption across sectors and firms. Press Release, 2025
- Market Data Forecast, Asia Pacific Artificial Intelligence (AI) Market Size Overview, 2024-2033. Report, 2025
- IDC, Worldwide Global DataSphere Structured and Unstructured Data Forecast, 2025–2029. Doc #US52800025, IDC, 2025
- IDC, Worldwide Global StorageSphere Forecast, 2025–2029. Doc #US53561425, IDC, 2025.
- Western Digital, Data Center Hard Drives
- Western Digital, Preparing for 30TB and Beyond—How Dual Actuators Can Help Make High-Capacity, High-Performance Hard Drives Possible. Blog, 2023
- PwC, Powering possibility: Closing the clean energy gap for Asia Pacific data centres. Report, 2025
- IMDA, Driving a Green Digital Future, Singapore’s Green Data Centre Roadmap, Report, 2024
- Energy Market Authority, Singapore Energy Lecture by Minister-in-charge of Science and Energy & Technology Dr Tan See Leng. Speech, 2025
Stefan Mandl is Vice President, Sales & Marketing for APJC, Western Digital.
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