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AIと生成AI

As agents, digital twins and Physical AI take on greater operational responsibility, manufacturers need governance that aligns autonomy with risk, accountability and trust

As manufacturers move AI from pilots into product development and production, competitive advantage will depend on connecting industrial data, digital twins, knowledge graphs and governed Physical AI

As engineering and manufacturing organizations move beyond AI experimentation, connected data, digital threads and contextual intelligence will be critical to delivering measurable business value
AI adoption is accelerating across Retail and CPG. Yet as organizations invest at unprecedented scale, many are struggling to turn AI ambition into measurable business impact.

A six-month FinOps case study on operational, governance and architecture savings beyond automated recommendations

Discover how Everyday AI embeds copilots, assistants and intelligent agents into workplace interactions to improve productivity, employee experience and outcomes.

Learn how AI agents automate enterprise workflows, coordinate tasks across systems and improve workplace productivity with governance and human oversight

We can build an AI-first workforce by combining AI, human judgment and workforce transformation to enhance productivity, develop future-ready skills and create more adaptive, intelligent workplaces
AI Force for Coding Agents governs Claude Code and Codex with compliance, audits, FinOps visibility and vetted skills, enterprise-ready AI coding, without shadow risk.

As Physical AI moves intelligence into cameras, sensors, robotics and Edge infrastructure, enterprises are beginning to build operations that can observe, interpret and act in real time
Discover how to scale enterprise AI to drive measurable value and competitive advantage
HCLTech transformed E.ON’s digital workplace with an AI-enabled platform that delivers faster information access and a better employee support experience