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NTT DATA Named Market Shaper for Physical AI Services

⏱️ 2 min read

NTT DATA has been recognized as a Market Shaper in the inaugural Gartner® Emerging Market Quadrant for Physical AI Services – Established Vendors. The report evaluates 27 providers in the emerging Physical AI Services (PAIS) market.

“Physical AI is transforming how organizations operate across industries, but success depends on deploying it securely and safely,” said Shahid Ahmed, Head of Edge Services, NTT DATA, Inc. “NTT DATA’s comprehensive portfolio of Physical AI solutions helps clients build more intelligent operations that improve productivity, strengthen operational performance and deliver measurable business value.”

“NTT DATA’s Physical AI story is grounded in applied innovation,” said Pietro Scarpino, Head of Applied Innovation for NTT DATA. “Our Global Innovation Center experiences showcase physical AI solutions, while production examples – such as Private 5G-enabled robotics and edge AI – prove how ideas move from demonstrations to real-world operations.”

NTT DATA Physical AI Services Highlights

  • Edge intelligence that brings AI closer to machines, sensors and workflows for real-time decision making.
  • Private 5G and advanced wireless connectivity to securely connect and coordinate AI-enabled systems.
  • Simulation, robotics and digital twins to design, test and orchestrate physical AI systems.
  • Lifecycle governance and observability to monitor, validate, update and continuously improve AI models and autonomous operations.
  • Enterprise-scale production and managed services spanning infrastructure, connectivity, design engineering, cybersecurity, IT/OT integration, change management and ongoing operations to help clients scale to production while reducing complexity, risk and cost.

NTT DATA said that it is already applying these capabilities across client environments. Examples include Private 5G-connected autonomous vehicles, machines and robots; quadruped robots for industrial inspections; AI-powered real-time anomaly detection; digital twin-based crack detection; and shop-floor task verification to improve operational efficiency and quality.

The full report is available here.


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