NTT DATA and Ericsson have announced a multi-year strategic partnership to accelerate enterprise adoption of private 5G and unlock advanced edge AI and physical AI use cases, enabling organisations to move from pilot projects to globally scalable, production-ready deployments.
Under the collaboration, private 5G will be delivered as a fully managed global service with consistent architecture, operations and security standards worldwide.
By combining Ericsson’s Private 5G and Edge platforms with NTT DATA’s full-stack enterprise network services, wireless expertise, IT/OT security and managed services capabilities, the companies aim to help enterprises embed real-time intelligence directly into connectivity infrastructure.
The partnership will focus on four priority areas: delivering global private 5G managed services at scale, embedding AI directly into enterprise connectivity, building repeatable industry solutions, and creating a unified global go-to-market model.
NTT DATA will act as Ericsson’s global system integration and managed services provider, ensuring standardised deployment and operational consistency across regions. NTT DATA Edge AI agents will run on Ericsson’s enterprise Edge platforms, enabling autonomous decision-making at the point where data is generated.
“Ericsson has been advancing enterprise connectivity for over a decade. This extends that capability to support edge AI and physical AI at scale across industries,” Asa Tamsons, Senior Vice President and Head of Business Area Enterprise Wireless Solutions, Ericsson, said.
Together, the companies will deploy private 5G, edge AI and physical AI solutions across industries, including manufacturing, mining, ports, airports, energy, transportation and smart cities, targeting measurable ROI and faster time to value.
“As enterprises adopt AI at the edge, they need partners who can bring connectivity, intelligence and security together in a way that actually works in production,” Shahid Ahmed, Global Head of Edge Services, NTT DATA, said.
The partnership will initially prioritise high-impact use cases such as automated quality inspection and predictive maintenance in manufacturing; autonomous routing and asset tracking in transportation and logistics; remote and AI-driven monitoring in energy and mining; and intelligent traffic and public safety systems in smart cities.
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