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Dell Technologies on Friday released an “AI India Blueprint” at the India AI Impact Summit 2026, outlining a framework to scale artificial intelligence infrastructure and governance as demand for compute accelerates.
The document argues that India must move beyond pilot projects and treat AI as national digital infrastructure, similar to earlier population-scale platforms. It aligns its recommendations with existing policy initiatives, including the IndiaAI Mission and data protection regulations, and focuses on execution rather than vision statements.
The blueprint highlights the scale challenge ahead. AI workloads in India are projected to grow at roughly 30% annually through 2030, with national compute demand potentially reaching 12–15 exa FLOPS by the end of the decade. Parallel to that expansion, data centres could account for up to 8% of India’s electricity consumption by 2030.
Dell has called for a defined national compute strategy with measurable capacity targets and region-specific deployment linked to innovation clusters. It also recommends expanding energy-efficient data centres, strengthening domestic electronics manufacturing and ensuring broader access to compute infrastructure for startups, academia and public institutions.
The company estimates India may require close to one million AI professionals by 2030. The framework proposes integrating AI literacy into mainstream education, expanding Centres of Excellence beyond large cities and building AI capabilities within the civil services.
On governance, it supports a principles-based regulatory model but calls for clearer operational standards, stronger cybersecurity baselines and wider adoption of Zero Trust architectures. It also flags the need for safeguards against model misuse, data poisoning and adversarial attacks as AI systems become embedded in critical sectors.
Vivek Mohindra, Senior Vice President at Dell Technologies, said India is at a “pivotal moment” in scaling AI. Manish Gupta, President and Managing Director, Dell Technologies India, said infrastructure readiness and security frameworks will determine how quickly AI deployments move to production scale.