Airtel bats for sovereign stack to process data from India
According to Airtel it would be incorrect to equate local data residency with data sovereignty as it is about controlling the data with a sovereign technology stack.
Bharti Airtel, the Indian telecom giant, has voiced concerns over the fragmented approach to data processing regulations in the country. Speaking at the Global Fintech Fest 2026, the company's Group CRO and Director of Corporate Affairs, Rahul Vatts, advocated for a sovereign cloud solution to control local data. Vatts clarified that equating local data residency with data sovereignty is incorrect, emphasizing the need to control data using a sovereign technology stack.
The government recently issued a circular on this matter, which Vatts described as a significant step forward. Over the past 30-45 days, the government has engaged in detailed discussions to determine the best approach. Vatts stressed the importance of having a clear discussion on the control plane and its management, as well as moving away from a fragmented policy approach.
While the government has stated that critical government data sets should be stored domestically, Vatts questioned why this approach should not apply to other critical sectors such as energy, health records, and personal identities. He argued that the policy should be consistent across all critical areas to ensure comprehensive protection.
As sectoral regulators start issuing enabling guidelines, Vatts highlighted that for critical workloads, the focus should shift from selecting any cloud to evaluating which cloud architecture offers end-to-end control under Indian law. Airtel is investing in building data centers with capacities of over 100 megawatts in the coming years and is placing significant emphasis on the demand for sovereign cloud infrastructure in the country.
With India generating the largest volume of data per consumer, averaging 38-40 GB per month, Vatts predicts that this figure will rise to 70-75 GB per customer within the next few years. This rapid growth in data generation underscores the need for robust data storage and processing solutions.
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