Choice is the new sovereignty: Powering India’s AI moment, from India to the world

India is stepping into a defining phase of its AI journey, moving from experimentation to execution. The India AI Impact Summit is expected to convene global leaders to make sense of that transition, with the government indicating it plans to launch indigenously developed AI models and democratise responsible AI adoption at scale.

Alongside that broader momentum, the ET AI Impact Forum is framed around the hard questions that separate ambition from outcomes: Who controls the infrastructure? How does compute scale affordably? How do enterprises align adoption with talent readiness and capital commitment? Those questions matter because AI is no longer a pilot running in a sandbox. It is becoming part of citizen services, banking, manufacturing, healthcare, and national critical infrastructure systems, where reliability, compliance, and continuity are non-negotiable.

This is where the conversation on AI sovereignty and digital sovereignty becomes real. Sovereignty is often misunderstood as a retreat into isolation. I see it differently: sovereignty is the ability to choose—where you run your enterprise software, where your data resides, how your AI models are governed, and how quickly you can adapt without external leverage. In an AI-first world, dependence can show up in many forms: a single deployment model, a single cloud dependency, a single jurisdictional exposure, or a single vendor’s roadmap becoming your organisation’s constraint. Sovereignty is the opposite of that; it’s freedom of movement.


At HCLSoftware, our sovereignty message is simple: choice is key. Not “cloud versus on-prem.” Not “global versus local.” But the practical flexibility to deploy across on-premises, sovereign cloud, hybrid, or regulated environments—while maintaining consistent security controls, observability, and policy enforcement. For many organizations, sovereignty starts with data residency. But it quickly expands into data security, operational autonomy, and AI governance because AI amplifies both opportunity and risk.

HCLSoftware, as one of the largest enterprise software product businesses headquartered out of Asia, serving thousands of customers worldwide, we’ve learned that sovereignty is not a niche requirement; it’s increasingly a baseline expectation. That scale matters because sovereignty can’t be an afterthought bolted onto products. It must be engineered into platforms, across identity, data, deployment, security, and lifecycle management.

This is also why we speak about our XDO Blueprint—orchestrating Xperience, Data, and Operations—as a practical fabric for the AI era. AI creates value only when it is embedded into workflows: improving experiences, turning data into intelligence, and making operations more adaptive and resilient. The Agentic Service as Platform (ASaP) mindset complements this: instead of relying on external dependencies to deliver outcomes, we build platforms that let enterprises operate AI as a governed capability: repeatable, policy-driven, and continuously improving.

Digital sovereignty is not a slogan; it’s an operating model built on choice. And in practice, that choice becomes real only when enterprises can standardize how they collaborate, how they secure and run operations, and how they turn data into intelligence, without losing control of where and how it all runs. Here are three areas to look at:
1) Sovereign AI and collaboration
Sovereign AI begins with trusted collaboration—because enterprise knowledge, decisions, and sensitive conversations live there. We are investing in collaboration solutions that prioritize data autonomy, secure communications, and flexible deployment. In regulated and critical environments, flexibility is a strategic requirement and not a preference.
2) Secure AI and intelligent ops
AI will expand the attack surface unless security and operations evolve together. Secure AI means protecting applications, endpoints, and operational workflows while using intelligence to reduce response time and improve resilience. “Intelligent Ops” is about applying AI where it counts: service stability, compliance posture, automation, and observability, so enterprises can scale confidently.
3) Data intelligence at scale
AI is only as good as the data it can trust. Data intelligence is not just analytics; it’s governance, lineage, quality, and discoverability across distributed estates. Sovereignty here means you can build intelligence while respecting residency, regulatory constraints, and domain boundaries, without fragmenting your data strategy.

When I join the ET AI Impact Forum panel, I’ll bring the enterprise product and platform perspective, the lens that determines how AI gets embedded into business workflows at scale. India’s AI future won’t be defined only by models; it will be defined by the platforms that operationalise those models securely, responsibly, and flexibly across industries and geographies.

India has an opportunity to lead with a distinct global proposition: “Made in India, for the World.” Not just as a slogan, but as a blueprint for digital independence where innovation thrives because organisations retain control, preserve choice, and build AI on trusted foundations. If you’re at the Summit, I look forward to the conversations about not just what AI can do, but how we ensure it is deployed on our terms.

Disclaimer: The opinions and views in the article are of Kalyan Kumar (Chief Product Officer of HCLSoftware) only, and provided for general information purposes. The news and editorial staff of ET had no role in the creation of this article nor vouch for or endorse this content.