Hitachi Report Examines Readiness for Physical AI in Industrial Companies

Hitachi, Ltd. (TSE:6501, "Hitachi") announced the release of its physical AI survey-based research report, Beyond the Pilot: Industry’s Physical AI Progression. The company surveyed over 200 global decision-makers from organizations operating in mission-critical industrial sectors including energy, manufacturing, transportation and logistics. The report explores how businesses today adopt AI in industrial use-cases, where they see the greatest value, and what it will take to scale toward physical AI deployments. Readers will gain practical insights on how to accelerate AI adoption while improving competitiveness, productivity, and long-term business performance.

After successfully transforming knowledge work, AI is now entering the physical systems that form society’s backbone: energy, industrial, and mobility infrastructure, to name a few. Given these systems’ reliability, safety, and regulatory requirements, there is no room for AI hallucinations. In short, AI technology applied to these systems must be deterministic, explainable, and auditable.

Based on the research findings, 97% of respondents use physical AI in industrial use-cases in some capacity today. Roughly half cite operational efficiency and productivity as their primary adoption drivers, with cost reduction close behind. However, while physical AI adoption is clearly ramping, only 8% of respondents note their operational deployments have reached the continuous optimization and innovation stage. This suggests that repeatable scale remains just out of reach.

Key findings:

• 87% of respondents associate delaying adoption with material risk. More than two-thirds view physical AI as very or extremely important to company goals, with some citing feeling extreme or high pressure to adopt. This suggests adoption speed is crucial to remain viable and competitive.

• 75% of respondents agree leadership actively supports AI initiatives though only 38% believe they are adequately resourced for adoption. This suggests a marked gap between strategic intent and practical AI readiness.

• Limited AI expertise (43%) and system integration challenges (31%) rank as the top barriers to adoption. Related, AI/machine learning ranks as the largest internal talent gap at 49%. Critical infrastructure equipment has a long lifespan and is viewed as aging in many sectors, suggesting it is not inherently AI ready. Therefore, system integration or total transition challenges are likely, making the right talent a must have.

• Use of physical AI to improve the laborer’s experience lags in comparison to other applications. Only an average 16% of respondents state significant AI usage by frontline workers and maintenance and repair teams via collaborative robots, smart PPE, and other human-centric applications. Meanwhile, nearly half indicate that these employees receive limited AI support, suggesting an opportunity to maximize AI return on investment.

• Most AI solutions in production are used in inspection and predictive maintenance applications, with process and supply chain optimization solutions nearing deployment. Notably, investment is shifting to behavioral analysis, smart computer numerical control (CNC) machines, and computer vision for safety – suggesting that AI project requests are evolving to support more complex physical AI use cases.*

“While many organizations have made meaningful progress with physical AI, scaling those capabilities across complex operational environments remains the next challenge. And one that must be solved to realize physical AI’s true benefits. Our research gives organizations a clearer understanding of where they comparatively sit today and where they can focus to achieve greater operational performance, resilience and long-term value,” said Rio Kurokawa, Chief Lumada Business Officer, HMAX Strategy Officer and Vice President of the AI Software & Services Business Unit, Hitachi, Ltd.

Hitachi leads in bringing the power of AI to industrial environments and critical infrastructure as demonstrated by HMAX, a suite of next-generation solutions that harnesses vast data from physical and digital assets, integrates advanced AI, and applies the company’s unmatched domain expertise. HMAX delivers deployable physical AI solutions among others that accelerate deployment and reduce risk associated with complex AI initiatives.

To learn more about the report and to download the findings, visit: www.hitachi.com/en-us/insights/articles/industrys-physical-ai-progression.

*Data referenced here reflects decision-maker responses from Manufacturing only.

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About Hitachi, Ltd.
Through its Social Innovation Business (SIB) that brings together IT, OT (Operational Technology) and products, Hitachi aims to be a global leader in continuously transforming social infrastructure through digital, contributing to a harmonized society where the environment, wellbeing, and economic growth are in balance.

Hitachi operates worldwide across four sectors – Digital Systems & Services, Energy, Mobility, and Connective Industries – as well as a Strategic SIB Business Unit focused on new growth areas. With Lumada at its core, Hitachi creates value by combining data, technology and domain knowledge to solve customer and social challenges.

Revenues for FY2025 (ended March 31, 2026) totaled 10,586.7 billion yen, with 606 consolidated subsidiaries and approximately 290,000 employees worldwide. Visit us at www.hitachi.com.

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