From AI Pilots To AI Factories: The Next Mandate For CIOs And CAIOs

Dilip Kumar is the President & Global Head of Infrastructure Solutions at NTT DATA.

​AI is rapidly becoming an operating model decision. The challenge facing most organizations today is the ability to deploy AI reliably, securely and at scale across core processes—from supply chains and manufacturing operations to financial operations, credit decisions and risk management.

A new reality is reshaping enterprise AI strategies. Growing regulatory scrutiny, geopolitical fragmentation, intellectual property concerns and data sovereignty requirements are driving organizations to shift toward private and sovereign AI.

Our survey of 2,567 senior executives across 35 countries and 15 industries discovered that 95% of respondents considered private or sovereign AI important to their AI strategy. Nearly as many are considering relocating AI infrastructure to specific geographies because of geopolitical concerns. Yet fewer than half feel fully confident in their ability to meet data sovereignty requirements for AI.

Private and sovereign AI are now becoming foundational requirements for trusted AI at scale.​ This shift is creating demand for an architectural construct: the enterprise AI factory.

Industrializing AI

An enterprise AI factory is an industrialized approach to developing, deploying, governing and scaling AI across the enterprise. Just as traditional factories transformed raw materials into consistent products, AI factories transform data into decisions through a repeatable, governed and economically viable operating model.

It enables organizations to retain full ownership of data, models and policies while delivering AI outcomes consistently across business functions and regulatory jurisdictions.

At its core, the AI factory brings together four interdependent layers:

• AI Services: Models, agents, retrieval systems, workflow automation and evaluation frameworks designed for enterprise reuse rather than isolated projects.