As AI moves beyond pilots, Dell Technologies sees India entering a new phase of enterprise adoption

India’s artificial intelligence (AI) journey is reaching a pivotal moment. After nearly two years of pilots, proofs of concept, and experimentation, enterprises are increasingly looking beyond AI as a technology showcase and towards deploying it at scale across business operations.

According to Venkat Sitaram, Senior Director and Country Head, Infrastructure Solutions Group, Dell Technologies India, the clearest indicator of this shift is that organisations are beginning to move AI initiatives into production environments.

“When you talk about inflection points, the first thing that comes to my mind is most pilots moving into production. And there are clear proof points. And that’s when you can really say that it has reached an inflection point because the adoption rate has gone up," Sitaram said in an interview with Dhruv Mohan of The Economic Times.


At the centre of this transition is the rapid emergence of agentic AI, which Sitaram believes is fundamentally changing how enterprises think about productivity, automation and business workflows.


“The biggest catalyst for this is agentic AI because the cognitive work of agentic AI when it starts running into your business workflows has changed dramatically. So it’s made analytics easy, it’s made coding easy, right? And you don't need so many human interventions,” Sitaram said.

For Indian enterprises, the challenge is no longer whether AI has potential, but how quickly they can turn that potential into measurable business outcomes.

Budgets, skills and prioritisation remain hurdles

Despite growing enthusiasm, enterprises continue to face familiar obstacles in scaling AI deployments.

“Budgets are not growing,” Sitaram said, describing cost pressures as a universal concern. Alongside funding constraints, he identified skills shortages and poor prioritisation of use cases as the two other major barriers slowing adoption.

“Number two, skills. Number three, lack of right prioritisation of use cases sometimes leads to longer experimentation cycles. And that’s where we see many of them have not progressed,” he explained.

However, he believes awareness around these challenges has improved significantly over the past year. Organisations are becoming more disciplined about identifying use cases with measurable outcomes rather than pursuing AI initiatives simply because of market hype.

At the same time, the nature of AI deployment itself is changing. Increasingly, inferencing is occurring at the edge, bringing intelligence closer to business users rather than relying entirely on centralised infrastructure.

“More and more inferencing is happening on the edge and that has become the business layer. What that would mean is you can have a simple edge device, an agentic edge device, and then start giving the power to that edge user.”

This shift is accelerating adoption across industries and reinforcing the importance of infrastructure planning.

Infrastructure becomes the foundation of AI strategy

As organisations scale AI initiatives, infrastructure is emerging as a critical differentiator.

“The adoption of AI is linked to technology infrastructure planning. And the right one size fits all approach will not work. You got to have rightly sized infrastructure,” Sitaram said.

Dell’s strategy reflects this view. The company recently launched PowerStore Elite, which Sitaram described as more than a conventional storage upgrade. “It’s not yet another storage array. It’s a data platform. It’s a modern data platform.” The platform incorporates AI-driven operational capabilities designed to automate workload management, optimise performance and streamline recovery processes. According to Sitaram, this allows enterprise IT teams to redirect resources away from routine operational tasks and towards higher-value initiatives.

“In PowerStore Elite with the AI ops integration, the IT operations work otherwise in managing workloads, placing the right workloads on performance and the recovery restore operations are all automated, made predictive.”
He also argued that AI is fundamentally reshaping the economics of enterprise storage as organisations seek to manage larger volumes of data and support increasingly sophisticated workloads.

“The economics of storage is changing in an environment. Who is changing the economics of the environment? Storage economics is AI.”

Future-proofing investments is another concern for enterprises making long-term infrastructure decisions. Sitaram highlighted lifecycle upgrade capabilities that allow organisations to adopt new generations of infrastructure without disruptive migrations.

“We’re telling customers that start with PowerStore Elite Gen 3 now and later if there is a Gen 4 that comes in after a few years, that can seamlessly coexist with this and you don’t need to have any disruption.”

Agentic AI is raising infrastructure demands

The rise of agentic AI is also increasing demands on enterprise infrastructure.

“AI demands a lot of compute power, highly optimised storage and last but not the least, high bandwidth network links,” Sitaram said.

In his view, all three foundational layers of enterprise technology, compute, storage, and networking, must evolve simultaneously to support the next wave of AI adoption.

Dell’s approach combines infrastructure with advisory services and pre-validated architectures intended to help organisations shorten deployment cycles.

“Pilot to production is the execution that you talk about. If you want pace, you need something that is qualified, ready, ready to use.”

The company engages customers through what it calls accelerated workshops, where business leaders and technology teams evaluate use cases, define measurable outcomes and develop implementation roadmaps. “We work with customers by engaging them with what we call an accelerated workshop. And in that workshop, we clearly discuss how and where they could start and what could be the outcomes, measurable outcomes, and use cases that need to be prioritised.” These engagements are often followed by visits to Dell briefing centres, where customers can examine real-world deployments, simulations, and reference architectures before committing to large-scale investments.

Making the economics work

For many organisations, the business case remains the deciding factor in AI adoption.

Sitaram believes enterprises are increasingly evaluating AI through the lens of productivity gains and operational outcomes rather than focusing solely on upfront costs.

“The cost of investment therefore becomes something that you can always invest and then take returns which are multi X in a certain period of time.”

While initial spending can appear substantial, he argues the returns can be transformative. “You’re delivering outcomes which are 100X. So on the 100X, a 2X investment in the initial stage may look maybe a little more, but once you see the cycle, then the results are phenomenal.”

To ease adoption, Dell is also promoting alternative financing models through Dell Apex, including consumption-based and pay-as-you-grow structures.

“We sometimes help customers do an Opex modeling of this, consume and pay as you grow models. And with the hand holding, so that is helping them get a quick fast start.”

Implementation timelines vary depending on architecture and workload requirements, but Sitaram said organisations are often able to deploy AI infrastructure within months rather than years.

“We’ve seen best cases varying anywhere a smaller implementation from 60 days and going up to 180 days.”

Private cloud and cyber resilience gain importance

As enterprises modernise their infrastructure, private cloud deployments are becoming increasingly relevant, particularly as AI workloads rely more heavily on containers and distributed architectures.

According to Sitaram, enterprises are looking for environments that offer flexibility, control and scalability while avoiding large upfront commitments.

“You’re not offloading too much in one go. You can buy as you grow.”

At the same time, cybersecurity concerns are intensifying as AI systems become more sophisticated. “AI adoption has increased the sophistication of cyber attacks. Newer and newer forms of attacks are emerging.” For that reason, Sitaram believes cyber resilience must underpin every AI strategy. “While AI is at the core, cyber resiliency should be the foundation layer.”

AI moves into the boardroom

Looking ahead, Dell expects AI adoption to expand well beyond large enterprises and regulated sectors.
“We’re seeing this catching up with even small, medium enterprises, AI startups.”

More importantly, AI is increasingly becoming a board-level priority rather than a purely technology-led initiative.
“Anywhere and everywhere you see there is a talk and buzz about how I can do and what I can do with AI, it's become board conversations, it’s become management meetings.”

Those conversations increasingly centre on competitive advantage.

“Are we leveraging enough? And are we seeing that as a competitive differentiator? Yes.”

For Dell, which has operated in India for nearly three decades, that shift signals a long-term opportunity. As enterprises move from experimentation to execution, the focus is increasingly turning towards infrastructure readiness, operational outcomes and the ability to scale AI responsibly. The companies that succeed, Sitaram suggests, will be those that can bridge the gap between ambition and deployment, and do so quickly.