The Japanese AI infrastructure market is currently at a major turning point. Until now, market growth has been driven by investments in AI infrastructure supporting model training. However, IDC expects a transition toward a phase of real-world deployment centered on inference. As AI adoption expands from proof of concept (PoC) to full-scale production, the role of AI infrastructure and the requirements placed upon it are undergoing significant changes. IDC positions 2026 as the inflection point from training to inference.
1. Rapid Growth of the Domestic AI Infrastructure Market and the Shift Away from a “Training-Centric” Model
In recent years, the Japanese AI infrastructure market has expanded rapidly. Backed by large-scale investments from hyperscalers and domestic cloud providers, the market recorded year-over-year growth exceeding 100 percent in both 2023 and 2024, more than doubling in size for two consecutive years. IDC forecasts that spending on Japanese AI infrastructure will reach 694.6 billion yen in 2025 and continue growing at a compound annual growth rate (CAGR) of 7.3 percent, approaching nearly 1 trillion yen by 2030.
However, the drivers of future growth will change significantly. In addition to traditional training workloads, demand for inference, where AI is continuously used within business operations, will expand and shift the market’s core focus. IDC predicts that by 2027, spending on inference in the Japanese AI server market will surpass that on training. Furthermore, from 2025 to 2030, the CAGR for inference-related spending is expected to exceed that of training by more than 10 percentage points.
2. Changes in AI Infrastructure Utilization Driven by the Expansion of Inference
According to IDC’s latest survey, Japan Digital and AI Infrastructure Strategies and Investment Survey 2026, public cloud accounts for the majority of AI infrastructure planned for inference use. At the same time, “private AI infrastructure,” including dedicated environments and edge deployments, represents 20 to 30 percent range of usage.
Meanwhile, only 22 percent of organizations are currently leveraging internal data for AI in a full-scale or advanced manner. This indicates that leading enterprises are just beginning to utilize internal data, including confidential and personal information, for AI applications.
IDC’s research shows that these early adopters intend to increasingly utilize private AI infrastructure going forward. This trend is driven by the need for optimized configurations tailored to specific business requirements, higher predictability in availability and costs, and the importance of addressing regulatory requirements and sovereign AI considerations. These organizations are building AI foundations that balance cost competitiveness with reliability while ensuring business continuity.
- Only 22 percent of companies are leveraging internal data extensively or at an advanced level for AI.
- Leading organizations in internal data utilization show a strong intention to adopt private AI infrastructure to enhance cost competitiveness and predictability while building reliable AI foundations that also account for sovereign AI.
As AI infrastructure becomes directly linked to national strategies and corporate competitiveness, addressing sovereign AI and data sovereignty is becoming increasingly important. From the perspectives of data protection, data residency management, and geopolitical risk mitigation, the use of dedicated environments and sovereign clouds is expected to expand.
3. Expansion of the AI Infrastructure Services Market and Changes in Competitive Dynamics
With the expansion of AI infrastructure adoption, the IT infrastructure services market covering deployment, operation, and maintenance is also experiencing rapid growth. The Japanese AI-related IT infrastructure services market is projected to grow from 95.7 billion yen in 2025 to 232.0 billion yen by 2030, achieving a CAGR of 19.4 percent. The increasing complexity of AI infrastructure, including requirements such as liquid cooling and advanced data center facilities, is driving demand for specialized services.
The competitive landscape is also changing. It is moving away from a traditional focus on hardware performance toward flexibility in infrastructure selection, service delivery capabilities, and the ability to support production-level AI deployment. While vendors that led with high-performance GPU-based infrastructure and related services have driven the market to date, IDC expects that companies capable of providing end-to-end support, from AI adoption and application development to hybrid environment operations and sovereign AI compliance, will establish a competitive advantage.
IDC has published a report analyzing changes in the Japanese AI infrastructure market in detail: Japan AI Infrastructure and Services 2026: The Shift in Competitive Dynamics Driven by Inference. This report provides a segmented market forecast from 2025 to 2030 to capture structural changes in the Japanese AI infrastructure market. It includes analysis by server and storage, service provider and enterprise, deployment model, and industry vertical. The AI server market is further segmented by training and inference as well as accelerated and non-accelerated servers.
In addition, the report presents forecasts for the Japanese IT infrastructure services for AI market by customer type and service type. It also examines changes in AI infrastructure demand and key vendor trends, clarifying future market opportunities and changes in the competitive landscape.
Through these analyses, readers can gain a comprehensive understanding of how demand structures are evolving from training to inference, differences in investment trends between service providers and enterprises, and emerging opportunities in the expanding services market.
