NTT DATA expands AI Factories with Cisco

NTT DATA describes the AI Factories as hands-on environments for determining how priority AI use cases can be deployed, secured, governed and operated at scale.[1] Organizations can evaluate workloads against real-world requirements, including infrastructure architecture, performance, workload placement and cost.[1] The company says its factories demonstrate applications in employee productivity, customer experience, intelligent operations, cybersecurity, networking, software development and industry-specific processes.[1] Engagements can include discovery workshops, technical deep dives, proof-of-concept planning and solution design.[1] These activities offer teams a way to examine technical and operational questions before deciding how to proceed.

NTT DATA launched new AI Factories in Paris and Singapore during October 2026; they join its sites in Plano, Texas, and Riyadh.[1] The company also launched its Munich AI Factory on October 7 in NTT Global Data Centers’ Munich 2 data center.[1] Unlike a traditional demonstration or innovation lab, the Munich facility operates in a live data-center environment.[3] NTT DATA says organizations can test AI they own and control against their own use cases there before investment decisions.[1] Enterprise and public-sector organizations can visit the Munich facility by appointment.[3]

NTT DATA says the factories combine its full-stack AI capabilities with partner technologies, including those from Cisco and NVIDIA.[1] Cisco Secure AI Factory with NVIDIA provides a secure and scalable infrastructure foundation for enterprise AI.[1] CRN reports that NTT will combine Cisco Cloud Control, networking, security and data-center technology into its own platform.[2] Cisco describes Cloud Control as an agentic AI platform designed to manage, monitor and defend critical IT infrastructure across domains.[2] The companies’ partnership spans 35 years, and NTT DATA characterizes its evolution as a shift toward AI outcomes through co-creation, co-selling and co-delivery.[2]

NTT DATA identifies infrastructure bottlenecks, governance concerns, security requirements, and uncertainty about operational costs and performance as reasons the move from AI pilots to production can stall.[1] Cisco’s Cassie Roach says enterprises need secure, resilient infrastructure that addresses security, performance and operations while preserving control of data and AI economics.[1] NTT DATA’s Dilip Kumar says AI infrastructure requires an agentic operating model in which people and AI agents work together to turn insights into actions.[2] Kumar also describes the opportunity as operating AI infrastructure differently through autonomous operations, rather than merely deploying AI.[2] NTT DATA says its approach is intended to help organizations manage complexity and turn AI investments into business outcomes.[1]