The global AI data center market size is projected to exceed USD 200 billion in 2025 and grow to USD 1 trillion by 2030, with a compound annual growth rate of over 40%.

Concurrently, several major US tech giants plan to invest approximately HKD 2.3 trillion collectively this year to establish new data centers, meeting the rapidly growing demand for AI applications.

This massive investment underscores the global tech industry's urgent need for AI computing infrastructure and signals the accelerated deployment of a core cornerstone for the digital economy era.

01 Market Overview: Size and Growth Drivers

Market research forecasts indicate that the global AI data center market size will increase from USD 17.54 billion in 2025 to USD 165.73 billion by 2034, achieving a CAGR of 28.34%.

This growth is primarily driven by three key engines: the generative AI boom, accelerated technological iteration, and global policy support.

According to IDC data, the global AI server market size is expected to surpass USD 31.79 billion in 2025, with a CAGR of 22.7%.

AI servers are contributing an increasingly prominent share of the overall market value, projected to account for 72% of the total server market value by 2025.

From a regional perspective, the North American market dominates, holding 43.3% of the global hyperscale data center market in 2024; the Asia-Pacific region is a clear growth engine, with an expected CAGR of 29.1%.

02 Giants' Competition: Tech Companies' Layout

As AI applications become more widespread and related enterprise businesses experience rapid growth, tech giants are increasing their data center investments.

Microsoft's latest results show that Azure and other cloud services revenue exceeded USD 75 billion in fiscal year 2025, a 34% increase, benefiting from rising AI demand.

To meet AI computational needs, US tech companies are accelerating investments in AI data centers.

Last month, NVIDIA and OpenAI announced a strategic collaboration, with the former investing HKD 780 billion to jointly build data centers equipped with millions of Graphics Processing Units.

The top eight global cloud service providers accounted for over half of AI server shipments in 2025, highlighting CSPs' dominant position in the AI infrastructure field.

The top five providers – Amazon, Microsoft, Google, Meta, and Alibaba – control approximately 60% of installed hyperscale megawatt capacity, generating significant design and procurement economies of scale.

From a capital expenditure perspective, the Capex of the top four North American CSPs will increase by over 30% in 2025, with continued future investment in GPUs or developing their proprietary ASICs.

03 Technology Frontier: Architectural Innovation and Efficiency Gains

Addressing the unique demands of AI workloads, data center technology is undergoing rapid iteration, primarily focused on architectural design, cooling technologies, and energy efficiency management.

AI training clusters are redesigning facility layouts; Google has already deployed 1 MW racks consuming +/- 400 VDC power.

Silicon shortages are prompting operators to secure multi-year GPU contracts, increasing construction timelines and capital intensity.

Technology differentiation is accelerating. Google's 1 MW rack immersion and direct-to-chip cooling offer a 30% energy efficiency differential compared to traditional air-cooling counterparts.

Microsoft is investing in small modular reactor PPAs to secure long-term zero-carbon baseload, a strategic move shielding against volatile energy markets.

Liquid cooling penetration leaped from 3.7% in 2021 to 28.5% in 2025, with power density per cabinet exceeding 50kW becoming an industry standard.

These technological innovations not only enhance computing density but also provide solutions for addressing the growing energy consumption challenges of data centers.

04 Future Outlook: Trends and Predictions

Looking ahead, the AI data center market will maintain rapid growth amidst challenges, exhibiting several distinct trends.

From a technical perspective, the trend of computing power democratization will accelerate, with distributed AI computing networks covering 80% of prefecture-level cities, achieving inference latency<20ms.<>

Breakthroughs in compute-in-memory and quantum-classical hybrid architectures will gradually commercialize, with memristor-based compute-in-memory chips potentially offering 100x improvements in energy efficiency.

Regarding application scenarios, inference server market share will surpass training server share for the first time in 2024, with inference demand in e-commerce/healthcare growing by 156%.

Hybrid cloud architecture becomes mainstream, with 70% of enterprises adopting a hybrid deployment model of public cloud + private AI servers.

Regional markets will show differentiated characteristics: Europe enjoys stable capital inflows, driven by sovereign requirements and Nordic renewable energy.

The "Sovereign Cloud" model transcends compliance, fostering local AI R&D and catalyzing regional hardware supply chains.

By 2028, AI servers are expected to account for approximately 20% of total annual server shipments, with a CAGR of nearly 24% from 2023 to 2028.