Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market Size
| Study Period | 2019 - 2030 |
| Base Year For Estimation | 2024 |
| Forecast Data Period | 2025 - 2030 |
| Market Size (2025) | USD 9.59 Billion |
| Market Size (2030) | USD 26.67 Billion |
| CAGR (2025 - 2030) | 22.69% |
| Market Concentration | Medium |
Major Players*Disclaimer: Major Players sorted in no particular order |
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market Analysis
The Asia-Pacific Artificial Intelligence Optimised Data Center Market size is estimated at USD 9.59 billion in 2025, and is expected to reach USD 26.67 billion by 2030, at a CAGR of 22.69% during the forecast period (2025-2030).
- In 2024, the Asia-Pacific (APAC) region's digital infrastructure is undergoing a significant transformation, primarily fueled by the swift incorporation of Artificial Intelligence (AI) into data center operations. As of 2024, the IT load capacity of traditional colocation data centers in the region surpassed 13,000 Megawatts (MW), boasting an average rack density of 7KW.
- This shift is especially evident in the APAC region, influenced by its unique characteristics: a vast and swiftly digitizing populace, the emergence of AI-centric startups, national agendas pushing for digital transformation, and substantial investments from international cloud giants. Countries like China, India, Singapore, Japan, and Australia are at the forefront, channeling resources into next-gen data centers, with AI capabilities embedded at their core.
- While conventional data centers in the region typically manage IT loads between 10–20 MW, AI-enhanced counterparts are now engineered to accommodate loads ranging from 100–200 MW and even higher. This surge in power density per square foot facilitates increased computing within the same power constraints. For example, AirTrunk's TOK2 in Tokyo is crafted for an IT load exceeding 110 MW, catering to AI and hyperscale cloud needs. Meanwhile, Yotta's NM1 in India boasts a scalable IT load surpassing 50 MW, with dedicated sections for high-performance GPU clusters tailored for AI tasks.
- Traditional data centers in APAC operate with 5–10 kW per rack. In contrast, AI-optimized facilities are now designed for 30–50 kW per rack, and in select instances, even 70–100 kW, particularly for GPU clusters. For instance, ST Telemedia Global Data Centres in Singapore is accommodating high-density AI racks, utilizing advanced liquid and hybrid cooling solutions. NEXTDC in Australia is rolling out racks reaching 50 kW, specifically to cater to AI demands in sectors like mining and fintech. Furthermore, CXO highlights the need for concentrated compute clusters in AI training and inference, noting a redesign of power delivery systems to handle IT loads double that of five years prior.
- Governments across APAC are enacting data localization laws, fostering the growth of localized, high-performance computing setups tailored for AI tasks. Concurrently, the expanding reach of 5G networks, the evolution of smart cities, the push for edge computing, and the embrace of Industry 4.0 are significantly amplifying the demand for AI-driven, low-latency, and scalable data centers.
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market Trends
Machine Learning Is Expected To Hold the Maximum Market Share
- Data centers are becoming smarter and more efficient, thanks to the pivotal role of machine learning (ML). By analyzing vast amounts of both real-time and historical data, ML optimizes operations, cuts costs, and boosts uptime. For instance, ML algorithms monitor variables like temperature, humidity, workload, and power usage, allowing for dynamic adjustments to cooling systems and airflow.
- Take Google, for example. The tech giant has harnessed DeepMind’s AI to fine-tune energy consumption across its data centers, including those in Singapore. This AI diligently sifts through both historical and live data—like temperature and power load—to make real-time adjustments to cooling systems. The outcome? A notable 30% drop in cooling energy use, a feat especially commendable given Singapore's tropical climate.
- Machine learning delves into sensor data from servers, HVAC systems, and electrical units, forecasting potential component failures. This proactive approach minimizes downtime and slashes maintenance expenses. NTT Communications, for instance, boasts an AI-optimized data center in Japan. Here, ML models spot anomalies in real-time, be it in power systems or cooling fans, leading to a 40% dip in unexpected outages and an extended equipment lifespan.
- DCIM systems powered by ML offer autonomous decision-making for monitoring, alerting, and controlling power and cooling systems. STT GDC, another player in Singapore, employs ML in its DCIM tools to foresee workload distributions, tweaking environmental systems in response. This savvy adjustment has led to a 15% boost in Power Usage Effectiveness (PUE).
- Across Asia-Pacific and the globe, machine learning stands as the cornerstone of AI-enhanced data centers. Whether it's refining energy and cooling efficiency, enabling predictive maintenance, or orchestrating workloads, ML is steering data center operations towards a smarter, greener, and more scalable future.
China is Expected to Dominate the Market throughout the Forecast Period
- China stands out as the foremost and most assertive player in the Asia-Pacific's AI-driven data center arena. Government Backing: In 2020, the Chinese government unveiled its "New Infrastructure Initiative," placing a premium on AI, data centers, 5G, and cloud computing. By 2025, China has set its sights on establishing over 200 national-level green and intelligent data centers. AI-Driven Infrastructure: Major players like Baidu, Tencent, Alibaba, and Huawei have rolled out hyperscale, AI-centric data centers. These facilities not only cater to sophisticated AI training tasks but also incorporate bespoke AI chips, including Huawei’s Ascend 910 and Baidu’s Kunlun processors.
- Take Baidu’s Yangquan AI Cloud Data Center in Shanxi, for example. It employs autonomous systems for power distribution, cooling, and workload management. This innovation allows it to train expansive LLMs (large language models) using 50% less energy than conventional centers. Alibaba’s premier data center in Hangzhou mirrors this AI-centric approach. Utilizing its in-house AIOps (Artificial Intelligence for IT Operations) platform, Alibaba harnesses machine learning to streamline tasks like fault detection, server health assessments, and energy management. This has led to an 80% reduction in human oversight for routine tasks, a 30% dip in power usage (achieving a PUE of 1.09), and uninterrupted services even during peak times like Singles’ Day
- Building on the "New Infrastructure" Initiative from 2020, China is channeling efforts into 5G, AI, Industrial IoT, and expansive data centers. Recognizing the significance of AI and data centers, the Chinese government has classified them as pivotal infrastructure, drawing in investments worth hundreds of billions of RMB from both state and private entities. As highlighted by the Ministry of Industry and Information Technology (MIIT) in 2022, “Data centers are the bedrock of the digital economy. AI should be at the heart of their operations.”
- Chinese data centers are increasingly leveraging ML for optimizing HVAC systems, enhancing airflow, and modulating workloads in real-time based on power availability. For instance, Tencent’s AI-driven data centers in Qingyuan have achieved a 30–40% reduction in cooling energy through advanced environmental modeling. Furthermore, the government is incentivizing AI-integrated, eco-friendly data centers in western regions through subsidies and tax reliefs. In Beijing, stringent PUE regulations require new data centers to maintain a PUE of 1.3 or lower. There's also a concerted push for AI chip innovation to lessen dependence on imported GPUs, especially in light of recent export constraints. With these concerted efforts, China is firmly establishing its dominance in the global landscape of AI-centric data center infrastructure.
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Industry Overview
In the Asia Pacific, the AI data center market is witnessing a consolidation trend. Key players such as Delta Electronics, Fuji Electric, Daikin Industries, and Huawei Digital Power Technologies Co., Ltd. are making their mark, alongside others like Inspur and Sunbird Software, Inc. The competitive landscape is not only fierce but also rapidly evolving. Chinese giants, including Huawei, Alibaba, and Baidu, lead with their vertically integrated solutions. In contrast, Japan and South Korea, with players like Fujitsu, Daikin, and Samsung, emphasize precision engineering and advanced components. Meanwhile, global entities such as Vertiv and Graphcore are broadening their presence in the Asia Pacific, further heightening the competition. The market dynamics are influenced by rising AI workload demands, a push for energy efficiency, and the burgeoning growth of edge computing. This environment particularly benefits players who leverage AI-native technologies, demonstrate regional adaptability, and forge strong ecosystem partnerships.
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market Leaders
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NVIDIA Corporation
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Huawei Technologies Co., Ltd.
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Sunbird Software, Inc.
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Delta Electronics
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Daikin Industries
- *Disclaimer: Major Players sorted in no particular order
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market News
- March 2025: Alibaba Cloud unveiled its newest addition to the "Qwen series" of artificial intelligence models. This launch comes amid intensifying competition in China's large language model arena, especially after the notable "DeepSeek moment." The newly introduced model, "Qwen2.5-Omni-7B," boasts multimodal capabilities, allowing it to handle diverse inputs such as text, images, audio, and video. In return, it generates instantaneous text and natural speech outputs.
- February 2025: Daikin has unveiled its latest offering, the Pro-C Computer Room Air Handler (CRAH), bolstering its Data Center product lineup. Tailored to cater to diverse cooling requirements of Data Centers, the unit boasts an enhanced design and sophisticated control mechanisms.
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Industry Segmentation
The term "Artificial Intelligence (AI) in data centers delves into the integration of diverse AI technologies, spanning machine learning, deep learning, natural language processing, and computer vision into the operations of data centers. These operations encompass a spectrum of components, from infrastructure and energy management to storage, networking, cybersecurity, and facility automation.
Asia-Pacific Artificial Intelligence (AI) Data Center Market Report is Segmented by Data Center Type (CSP Data Centers, Colocation Data Centers, and Others(Enterprise and Edge), by Component (Hardware(Power, Cooling, IT Equipment, and Others), Software Technology (Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision)), and Services, and by Country (China, India, Japan, Malaysia, Australia, Singapore, Indonesia, Thailand, South Korea, and Rest of Asia-Pacific). The Market Sizes and Forecasts are Provided in Values (USD) for all the Above Segments.
| By Data Center Type | CSP Data Centers | ||
| Colocation Data Centers | |||
| Others (Enterprise and Edge) | |||
| By Component | Hardware | Power | |
| Cooling | |||
| IT Equipments | |||
| Others | |||
| Software Technology | Machine Learning | ||
| Deep Learning | |||
| Natural Language Processing | |||
| Computer Vision | |||
| Services - (Managed Services, Proffesional Services, etc) | |||
| By Country | China | ||
| India | |||
| Japan | |||
| Malaysia | |||
| Australia | |||
| Singapore | |||
| Indonesia | |||
| Thailand | |||
| South Korea | |||
| Rest of Asia-Pacific | |||
| CSP Data Centers |
| Colocation Data Centers |
| Others (Enterprise and Edge) |
| Hardware | Power |
| Cooling | |
| IT Equipments | |
| Others | |
| Software Technology | Machine Learning |
| Deep Learning | |
| Natural Language Processing | |
| Computer Vision | |
| Services - (Managed Services, Proffesional Services, etc) |
| China |
| India |
| Japan |
| Malaysia |
| Australia |
| Singapore |
| Indonesia |
| Thailand |
| South Korea |
| Rest of Asia-Pacific |
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Market Research FAQs
How big is the Asia-Pacific Artificial Intelligence Optimised Data Center Market?
The Asia-Pacific Artificial Intelligence Optimised Data Center Market size is expected to reach USD 9.59 billion in 2025 and grow at a CAGR of 22.69% to reach USD 26.67 billion by 2030.
What is the current Asia-Pacific Artificial Intelligence Optimised Data Center Market size?
In 2025, the Asia-Pacific Artificial Intelligence Optimised Data Center Market size is expected to reach USD 9.59 billion.
Who are the key players in Asia-Pacific Artificial Intelligence Optimised Data Center Market?
NVIDIA Corporation, Huawei Technologies Co., Ltd., Sunbird Software, Inc., Delta Electronics and Daikin Industries are the major companies operating in the Asia-Pacific Artificial Intelligence Optimised Data Center Market.
What years does this Asia-Pacific Artificial Intelligence Optimised Data Center Market cover, and what was the market size in 2024?
In 2024, the Asia-Pacific Artificial Intelligence Optimised Data Center Market size was estimated at USD 7.41 billion. The report covers the Asia-Pacific Artificial Intelligence Optimised Data Center Market historical market size for years: 2019, 2020, 2021, 2022, 2023 and 2024. The report also forecasts the Asia-Pacific Artificial Intelligence Optimised Data Center Market size for years: 2025, 2026, 2027, 2028, 2029 and 2030.
Asia-Pacific Artificial Intelligence (AI) Optimised Data Center Industry Report
Statistics for the 2025 Asia-Pacific Artificial Intelligence (AI) Optimised Data Center market share, size and revenue growth rate, created by Mordor Intelligence™ Industry Reports. Asia-Pacific Artificial Intelligence (AI) Optimised Data Center analysis includes a market forecast outlook for 2025 to 2030 and historical overview. Get a sample of this industry analysis as a free report PDF download.
