NTT Data’s expanded partnership will focus on agentic AI deployment at scale, leveraging AWS cloud technologies.
NTT Data
Artificial intelligence has become omnipresent in Big Tech marketing, framed as a transformative force reshaping every corner of the enterprise. In practice, however, many organizations remain constrained by far more basic challenges: aging legacy systems, fragmented data estates, and persistent uncertainty about how agentic AI fits into everyday workflows.
According to industry reports, 62% of U.S. organizations still rely on legacy software, with roughly 75% of IT budgets consumed by maintenance rather than innovation. But NTT Data’s latest move suggests a more deliberate response to that challenge.
On Jan. 29, the technology conglomerate announced a multi-year strategic collaboration agreement with AWS to accelerate enterprise cloud modernization and the responsible adoption of agentic AI. The emphasis is execution — centered on modernizing mission-critical workloads, building cloud-compliant foundations, and unlocking business value from AI investments in regulated and high-growth markets.
At the core of the partnership is a shared recognition that cloud transformation and AI adoption can no longer proceed in parallel lanes. Enterprises that merely lift and shift their existing applications to the cloud often struggle to deliver material returns. NTT Data and AWS are instead framing their collaboration around AI-driven modernization, with a focus on large-scale transformations of on-premises environments in industries where technical debt and regulatory pressures often hinder innovation.
“We’re shaping industry architectures, including pre-integrated business components, data models and AI agents, rather than waiting for requirements to be handed down,” Sudhir Chaturvedi, Chief Growth Officer and North America CEO of NTT Data, told me. “Agentic AI requires a fundamentally different governance model than traditional automation. Our platform-driven approach is governance-by-design, not governance as an afterthought.”
Industry Clouds As The Scalable Path To Enterprise AI
Rather than offering one-size-fits-all solutions, the collaboration leans heavily on industry-specific cloud platforms. NTT Data will expand its Industry Cloud offerings on AWS, which already boasts over 500 industry-specific, reusable business components and AI agents.
Financial services, healthcare and life sciences, public sector, manufacturing, retail, and energy industries are among the first to benefit. In each industry, the goal is to provide repeatable, compliant architectures that can be deployed faster than custom-built solutions.
For financial services institutions, this means improving core business systems and compliance processes while minimizing operational risk. In the healthcare and life sciences industries, the goal is to provide secure, AI-driven data platforms that can uncover hidden insights within complex application environments and speed research. Public sector deployments emphasize private and sovereign cloud configurations that meet strict compliance and data residency requirements.
“NTT’s Industry Cloud platform—with 500+ business components built on AWS—enables enterprises to adopt technologies like Amazon Bedrock and our modernization tools with proven implementation expertise,” Greg Pearson, VP Global Sales at AWS, told me. “The collaboration accelerates adoption through industry-specific solutions—AI-driven contact centers on Amazon Connect, intelligent operations using AWS IoT and analytics services, and managed services leveraging AWS automation.”
NTT Data and AWS recently expanded their collaboration around Amazon Connect, aiming to modernize contact centers and accelerate the adoption of AI-driven customer experience solutions globally. Agentic AI is positioned as an operational layer — automating routine interactions, supporting agents with real-time intelligence, and improving service consistency at scale.
“NTT Data’s Migration Factory approach runs entirely on AWS, using AWS’s Application Migration Service, Database Migration Service, and modernization tools. They’re integrating generative AI capabilities from Amazon Bedrock and agentic AI to automate manual processes. For mainframe modernization, they use AWS Mainframe Modernization alongside their implementation expertise to transform legacy systems into cloud-native applications on AWS,” explained Pearson.
For global support operations, the promise is lower costs, higher resilience, and more adaptive customer engagement without sacrificing governance.
Early customer examples include Honda Trading Asia, which recently migrated to AWS with the help of NTT Data, modernizing its systems and infrastructure while staying within tight timelines and budgets. According to NTT, Honda Trading Asia was operating under tight timelines and cost constraints, with limited ability to scale or standardize operations across its Asia-Pacific footprint.
“Honda Trading Asia executed a phased migration to AWS, moving more than 125 workloads and 158 TB of data without disrupting the business. The transition improved operational consistency across seven countries, while delivering a 24% reduction in infrastructure costs,” said Chaturvedi.
One of the most significant strategic aspects of the partnership centers on digital sovereignty. As a launch partner of the AWS European Sovereign Cloud, NTT Data will provide sovereign-by-design cloud solutions and managed services to European governments and businesses facing stringent data residency, compliance, and operational sovereignty requirements.
The objective is to eliminate the existing trade-off in regulated industries to access the innovation of hyperscale clouds without giving up control. The timing is deliberate, as with intensifying regulatory scrutiny and technology budgets under pressure, enterprises are increasingly seeking partners that can move AI from promise to production at scale.
For NTT Data and AWS, the wager is that agentic AI—when embedded directly into cloud modernization efforts and industry-specific workflows—can evolve into a durable growth engine rather than another stalled pilot. The real test will come as customers attempt to operationalize these architectures across complex, regulated environments. For now, the structure of the partnership suggests a clear-eyed understanding of what that challenge demands.