Over a single weekend, the enterprise technology world got a critical wake-up call. A prominent proprietary AI vendor abruptly disabled global access to its cloud-hosted flagship models. A government export control directive demanded swift compliance, and because the provider could not cleanly separate domestic users from international ones on the fly, it pulled the plug for everyone, everywhere. This is a critical wake-up call for enterprises worldwide; if your AI strategy runs entirely on a proprietary SaaS API, you are operating with an external kill-switch over your business. India’s regulatory and sovereign-AI momentum is your chance to derisk. The regulatory and political merits of that directive are a matter for policymakers. The operational lesson for Indian enterprises is far more immediate.

For Indian CIOs, CISOs, and boards, AI has clearly moved well past the pilot stage. It is now a core operational dependency. That raises an uncomfortable question most business continuity plans have not yet answered: if your external AI provider goes dark tomorrow, what happens to your business? Do your operations grid to a halt, or do you have resiliency plans in place?

The execution gap

This disruption exposes a deeper disconnect in how enterprises build their stacks. A global research, Navigating Digital Resilience, found a striking execution gap. A near-universal 98% of IT leaders treated digital sovereignty as a critical objective, yet only 52% have taken practical steps towards it. Driven by intense market pressure, 70% of organisations funnelled additional budgets into AI. In the rush to deploy, too many are building on rented ground: fragile, closed architectures stood up before the sovereign foundations that would protect them.

India is a notable exception to the complacency. In our research, 62% of Indian organisations are actively investing in digital sovereignty as a strategic priority, the highest among any of the markets we studied. That instinct is well-founded, because the ground beneath Indian enterprises has shifted decisively.

Why India’s case is sharper and its options stronger

With the Digital Personal Data Protection Rules notified in November 2025, the DPDP framework is now operational and moving through phased enforcement towards full compliance in May 2027. For Significant Data Fiduciaries, the obligations go beyond consent and breach reporting: the rules contemplate restrictions on transferring specified personal data outside India and require due diligence to ensure algorithmic systems do not put citizens’ rights at risk. An AI pipeline that pushes sensitive data into an opaque, externally controlled model sits awkwardly against that direction of travel. For example, if it becomes a legal mandate in future to not use public AI providers or to host AI workloads on public software clouds for data sensitive use-cases, that increases the level of risk for Indian enterprises exponentially.

At the same time, India is building genuine alternatives. The IndiaAI Mission, backed by more than ₹10,000 crore, has put tens of thousands of GPUs into a shared national compute pool and commissioned a wave of locally developed foundation models. Players such as Sarvam and BharatGen have released open, India-built models tuned for Indian languages; the government is now extending the UPI playbook to AI, aiming to make ready-to-deploy models as accessible to MSMEs as digital payments. For the first time, sovereign and open-weight options are not a compromise; they are a credible, fast-improving part of the stack.

That combination is unusual. Indian enterprises face sharper regulatory pressure to control their data, and a maturing ecosystem of independent, open alternatives to control it with. The rented-ground risk is higher here, but so is the opportunity to design it out.

Independence through choice, not isolation

None of this argues for abandoning global partnerships. A multi-vendor AI approach remains smart. The goal is not to build something that never breaks but to build something you can fix, move, or rebuild yourself when it does.

Over the next five years, 64% of technology leaders say transparency, control over model training, and data provenance will be the single biggest driver of digital resilience. Resilience of that kind cannot be a reactive security checkbox bolted on afterwards. It has to be designed into the core of the architecture.

Open source is the most durable path to that control. It offers the freedom to pivot when a vendor, a government, or a market moves against you, and continuous access to community-driven innovation without lock-in. True sovereignty, and operational resilience, means having the physical capability to run, secure, and manage your models on your own terms on-premises, or within compliant, localised sovereign clouds, whatever your regulatory and commercial reality demands.

India’s organisations should embrace a Private Enterprise AI methodology. As a blueprint for true sovereign infrastructure, Private Enterprise AI coexists with international vendor ecosystems whilst securing the local capability to operate technology independently. Adopting this framework through secure, hybrid, and open-source alternatives provides the platform independence, resilience, and genuine autonomy that today’s compliance landscape demands.

If that June weekend gave your leadership team even a moment’s pause, use it. Ask the one question that matters: how exposed is our AI infrastructure to a decision we do not control, and are we ready to build a foundation that can withstand it, and guarantee our operational independence?

The author is Rhys Oxenham, VP & General Manager AI at SUSE.

Disclaimer: The views expressed are solely of the author and ETCISO does not necessarily subscribe to it. ETCISO shall not be responsible for any damage caused to any person/organization directly or indirectly.

Join the community of 2M+ industry professionals.

Subscribe to Newsletter to get latest insights & analysis in your inbox.

All about ETCISO industry right on your smartphone!