Why India's AI ambitions demand a reset in virtualisation strategy

AI adoption accelerates across sectors, India must rethink virtualisation models to ensure cost efficiency, flexibility, and secure infrastructure capable of supporting scalable and inclusive growth

India’s digital growth is entering a new phase, one defined by AI at scale. Under the IndiaAI Mission and the vision of Viksit Bharat, AI is moving from pilots to production across banking, healthcare, agriculture, and governance.

 

For over a decade, virtualisation, has underpinned this digital expansion, enabling cloud adoption and modern data centres. But AI places new demands on that foundation. Workloads are now distributed, data-heavy, and cost-sensitive, running across core, cloud, and edge. As enterprises adapt, many are reassessing whether traditional virtualisation models (VMs) provide the flexibility and cost-efficiency needed for the AI decade.

 

This ongoing shift is what many now call the “Great VM Reset.”

 

The Great VM Reset: Why it is happening

The Great VM Reset is not about abandoning virtualisation. It is about updating it for new realities, making infrastructure more modular, cost-transparent, and adaptable. At the recent ImpactAI summit, what stood out was that all experts noted that the biggest constraints to AI deployment are no longer GPUs alone, but the rigidity and cost of the underlying systems that orchestrate them. 

Licensing models and bundled offerings have evolved, and many Organisations now face higher or less predictable costs. While large enterprises may manage this, startups, MSMEs, and public institutions need greater certainty and flexibility. If infrastructure costs remain unpredictable, AI adoption will concentrate in a handful of large enterprises, undermining the inclusive intent of the IndiaAI Mission.

 

Security is another concern. In India, government advisories have flagged vulnerabilities in widely deployed virtualisation platforms. When financial systems, public services, and government networks rely on these layers, resilience becomes critical.

 

AI intensifies these pressures. AI applications sit directly on the virtualisation layer. If that base is rigid or expensive to scale, innovation slows. 

Consider this analogy. Traditional virtualisation was like an older train with large coaches divided into cabins. It worked well for years. But as travel needs changed, not every passenger required the same journey. Some needed shorter routes or flexible tickets. If everyone must pay for the whole coach, the system limits new travellers.

 

The Great VM Reset is about modernising that railway. It allows organisations to choose what they need, pay for what they use, and move forward with greater confidence in cost and security.

How hybrid infrastructure makes it work

If the Great VM Reset defines the direction, hybrid virtualisation makes it practical. For India, this shift is less about technology preference and more about enabling AI deployment at national scale.

 

Hybrid virtualisation allows Organisations to continue running familiar virtual machines while gaining flexibility in how workloads are deployed and managed. It connects private data centres, public cloud, and edge environments in a unified model.

 

In the same way, hybrid virtualisation reduces unnecessary layers between applications and hardware while preserving governance and security.

 

The key benefit is flexibility.

 

Organisations can scale resources up or down as needed. They can modernise gradually rather than replace everything at once. They can avoid paying for capacity they do not fully use. And they can decide where workloads run based on cost, compliance, and performance needs.

 

For India, this flexibility is essential. The IndiaAI Mission aims to extend AI beyond large enterprises to startups, research institutions, MSMEs, and government bodies across the country. That requires infrastructure that is secure, sovereign, and economically sustainable. It must work in central data centres and in smaller facilities across states and districts.

 

Hybrid virtualisation supports this inclusive approach. It strengthens cost control, improves resilience, and helps ensure AI growth is distributed, not concentrated in a few hubs.

 

But scale and distribution alone are not enough. As AI becomes embedded in critical systems, the question is not just where it runs, but how securely and sovereignly it runs.

Building a secure base for AI for All

The Great VM Reset is more than a technical shift. It is a strategic step toward building a secure and sovereign digital base for India’s AI future. AI sovereignty cannot be achieved on infrastructure models designed for a different decade.

 

As AI powers banking, healthcare, agriculture, and governance, the infrastructure beneath it must be secure by design. India cannot democratise AI if the systems supporting it are vulnerable or difficult to scale. Modern hybrid compute strengthens the base layer, protects data, and supports compliance and localisation needs.

 

It also supports inclusion. Modular and cost-efficient infrastructure lowers barriers for smaller institutions and emerging enterprises. It allows participation from Tier-2 and Tier-3 cities and ensures that India’s growing AI talent works on flexible systems built for the future.

 

India’s AI ambition is bold. But leadership will depend not only on algorithms, but on the strength and sovereignty of the infrastructure beneath them. The Great VM Reset is about preparing for what comes next, building a digital backbone that is secure, adaptable, and ready to fuel India’s AI decade. The next phase of India’s AI journey will be decided not just by models and data, but by the infrastructure choices leaders make today. 

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(The author is  senior vice president and managing director, HPE, India)  (Disclaimer: These are personal views of the writer. They do not necessarily reflect the opinion of www.business-standard.com or the Business Standard newspaper)