Hitachi Report Examines Readiness for Physical AI in Industrial Companies
AI adoption progress, trends, and emerging priorities suggest opportunities and challenges for physical AI acceleration
SANTA CLARA, Calif., October 22, 2026--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.