Hitachi Establishes Global NVIDIA AI Factory for Physical AI Innovation

This analysis is based on Hitachi’s official press release [1] published on September 25, 2025, announcing the establishment of a global AI Factory built on NVIDIA’s AI Factory reference architecture.

Hitachi’s strategic initiative combines NVIDIA’s cutting-edge AI infrastructure with the company’s deep operational technology expertise to accelerate physical AI development across core business sectors. The AI Factory features Hitachi iQ systems with NVIDIA HGX B200 platforms powered by Blackwell GPUs, representing a significant investment in next-generation AI computing infrastructure with global distribution capabilities.

The AI Factory architecture demonstrates comprehensive integration of hardware and software components:

• Hitachi iQ with NVIDIA HGX B200 systems featuring Blackwell GPUs delivering 9 petaFLOPS FP4 performance per GPU [1][3][4]
• Hitachi iQ M Series with NVIDIA RTX PRO 6000 Server Edition GPUs for specialized workloads [1]
• NVIDIA Spectrum-X Ethernet networking platform for high-speed data transfer [1]

• NVIDIA AI Enterprise for production-grade AI applications [1]
• NVIDIA Omniverse libraries for simulation and digital twin development [1]

The infrastructure provides up to 144 petaFLOPS total FP4 performance per HGX B200 system, representing a 3X training performance improvement over previous generations and 15X inference performance enhancement compared to H100 systems [2][3][4].

The AI Factory’s distributed architecture across the United States, EMEA, and Japan enables Hitachi engineers to collaborate seamlessly with low-latency access to computing resources regardless of geographic location [1]. This global distribution strategy supports Hitachi’s Lumada 3.0 vision for digital transformation and enables both DX (Digital Transformation) and GX (Green Transformation) initiatives across the organization.

The initiative targets the rapidly expanding physical AI market, which is experiencing substantial growth:

• AI in Robotics Market: $25.02 billion in 2025, projected to reach $126.13 billion by 2030 (13.10% CAGR) [5]
• Physical AI investments exceeded $16 billion in the first three quarters of 2025 [6]
• Manufacturing and assembly represent 41% market share, with automotive at 28% [5]

Hitachi’s HMAX family of AI-enabled solutions will leverage this infrastructure for railway operations, energy grid optimization, industrial automation, and mobility applications [1].

Hitachi’s unique positioning combines IT expertise, OT domain knowledge, hardware capabilities, and AI integration through the Lumada 3.0 operating model [1]. This full-stack integration differentiates Hitachi from competitors who typically specialize in either industrial automation or AI software development.

The recent acquisition of German data and AI services firm synvert on September 24, 2025, demonstrates Hitachi’s comprehensive approach to accelerating Agentic AI and Physical AI development [1]. This acquisition, combined with the NVIDIA AI Factory, creates a powerful ecosystem for industrial AI innovation.

The AI Factory initiative represents a fundamental shift toward AI-driven industrial automation replacing traditional automation systems. This transformation enables:

• Software-defined physical systems with continuous learning capabilities
• Enhanced predictive maintenance for industrial equipment
• Improved operational efficiency across manufacturing and energy sectors
• Accelerated autonomous system development for mobility applications

The infrastructure addresses the competitive landscape where the top four industrial robot vendors (Fanuc, ABB, KUKA, Yaskawa) collectively held 57% market share in 2024 [5], indicating opportunities for software-driven innovation.

• Coordinating distributed AI infrastructure across global regions presents significant technical challenges
• Integration with existing Hitachi OT systems requires careful compatibility management
• Production scale-up of Blackwell GPU-based systems may encounter supply chain constraints

• Industrial customers typically have longer adoption cycles for transformative technologies
• Market reception depends on demonstrated ROI from early deployments
• Traditional industries require significant education and training to leverage physical AI capabilities

• Rapid growth in physical AI investments creates favorable market conditions
• Increasing demand for intelligent automation across industries supports adoption
• Healthcare sector showing fastest growth at 26% CAGR (2025-2030) [5]

• Full-stack integration capability provides significant differentiation
• Established customer relationships in traditional industrial markets offer entry points
• Global infrastructure with regional deployment capabilities supports scalable growth

• Physical AI applications in mobility and industrial settings face evolving regulatory frameworks
• Safety certifications for AI-controlled physical systems require extensive testing
• Data privacy and security compliance requirements for industrial AI systems

• AI factory infrastructure requires significant ongoing investment in hardware and software updates
• ROI timelines may be longer than traditional IT investments due to integration complexity
• Rapid technology advancement may require frequent infrastructure updates

Hitachi’s NVIDIA AI Factory represents a comprehensive strategic initiative that positions the company at the forefront of physical AI innovation. The infrastructure combines NVIDIA’s Blackwell GPU technology with Hitachi’s industrial expertise to create a global platform for AI-driven automation and intelligence.

The initiative targets the rapidly growing physical AI market, with particular focus on manufacturing, automotive, healthcare, and logistics sectors. The global deployment strategy across the US, EMEA, and Japan enables seamless collaboration and resource access for Hitachi engineers worldwide.

Success will depend on effective execution of the global deployment strategy, demonstrated value to industrial customers, and the ability to navigate the complex competitive landscape of industrial AI. The timing appears favorable given the rapid growth in physical AI investments and increasing demand for intelligent automation across industries.