Five key takeaways from Dell Technologies Forum 2026 in Mumbai

Five key takeaways from Dell Technologies Forum 2026 in Mumbai

AI infrastructure is moving to production scale as sovereignty, endpoint computing, consumption models and workforce skills shape enterprise technology decisions.

AI was a central theme at Dell Technologies Forum 2026 in Mumbai, but the discussions went beyond GPUs and data centre capacity. Across sessions involving Dell Technologies, L&T Vyoma and financial-services customers, the discussions highlighted how enterprises are approaching the next stage of technology adoption.

AI infrastructure is moving towards larger-scale deployments, organisations are paying closer attention to where workloads and data reside, AI is extending to the devices employees use, and infrastructure spending is being linked more closely to business requirements. The forum also put attention on the skills needed to support this transition.

AI infrastructure is moving from pilots to factory-scale deployments

The scale of AI infrastructure being developed in India is changing the requirements for building and operating compute environments.

L&T Vyoma’s managing director, Prashant Chiranjive Jain, discussed the company’s move from data centres and colocation towards AI factories, including its deployment of a 10,000-GPU NVIDIA B300 AI Factory at its Chennai data centre campus. L&T has described the deployment as India’s largest single-cluster AI infrastructure, designed to support large-scale inference, fine-tuning and training workloads.

The deployment requires more than adding GPUs to an existing data centre. Jain discussed the work involved across power, cooling, networking and storage, as well as the design and testing required to support high-density AI infrastructure.

The Chennai campus currently has 30MW of capacity, according to Jain’s discussion at the forum, while the broader site is being developed for significantly greater capacity. L&T Vyoma, Dell Technologies and NVIDIA have worked together on the infrastructure design, including areas such as power, cooling, networking and storage.

The project illustrates how AI infrastructure is becoming an engineering challenge across multiple layers of the technology stack. The ability to deploy and operate high-density AI environments requires coordination across compute, power, cooling, networking, storage and infrastructure operations.

For the ecosystem, that puts attention on capabilities beyond the supply of servers and GPUs, including infrastructure design, deployment, integration and ongoing operations.

Sovereignty is becoming part of the AI infrastructure discussion

Control over data, infrastructure and workloads was another theme in the discussion around AI infrastructure.

L&T Vyoma has positioned sovereign infrastructure as part of its AI and cloud strategy. The company describes its business as a sovereign AI cloud and hyperscale data centre platform, with its sovereign cloud designed to address data sovereignty, regulatory compliance and secure AI adoption.

At the forum, Jain spoke about the importance of owning and operating the technology stack and securing workloads within sovereign borders. The discussion also covered the role of an orchestration layer and an end-to-end infrastructure stack in allowing customers to operate workloads securely.

The requirement is particularly relevant to organisations handling sensitive or regulated workloads, where decisions around infrastructure also involve data location, security, control and compliance.

This makes sovereignty an infrastructure consideration rather than only a policy or regulatory issue. It also creates a requirement for technology providers and partners that can support customers across infrastructure, security, compliance and operations.

AI is moving closer to the employee

AI is also extending beyond the data centre and cloud to the devices employees use every day.

In her session, Jacinta Quah discussed how intelligence will span the data centre, the cloud and increasingly the desk. The discussion focused on AI PCs, on-device workloads, endpoint security and device management, placing the PC within the wider enterprise AI architecture.

Dell’s approach is to match different workloads with the appropriate compute environment. The company has positioned AI PCs as a way to bring AI capabilities into everyday workflows, while workstations address more specialised and compute-intensive workloads.

At the forum, Quah also discussed the need to bring AI closer to users while maintaining control over security, data and device management.

“The modern workplace is not separate from the strategy; it is where the strategy becomes real,” Quah said.

This puts the endpoint into the broader AI deployment conversation. As organisations introduce AI into everyday workflows, IT teams also need to consider how AI-enabled devices are deployed, secured and managed alongside existing enterprise infrastructure.

For partners, this connects AI with existing workplace technology, endpoint security and device management engagements.

Infrastructure spending is moving closer to business consumption

The financial-services discussions at the forum highlighted how customers are approaching infrastructure investment as their businesses grow.

Rahul Dayal, CTO, SBI Funds Management, discussed the company’s technology transformation as the mutual fund business expands. The organisation has adopted a hybrid architecture, combining cloud capabilities with infrastructure that remains on premises for workloads and data that require it.

The company is also using Dell APEX as a consumption-based infrastructure model. The approach allows SBI Funds Management to align infrastructure capacity and spending more closely with current business requirements and increase capacity as the business grows.

The discussion reflects a practical infrastructure challenge for financial institutions. Business growth can increase technology requirements quickly, while organisations still need to balance scalability, availability, cyber resilience and cost.

SBI Funds Management’s experience also shows why infrastructure architecture is becoming a business decision rather than simply a technology procurement exercise. The organisation has been transforming its architecture while considering where workloads should run and how much infrastructure capacity it needs at different stages of growth.

For technology partners, this creates scope around hybrid infrastructure, capacity planning, integration and ongoing management as customers move towards more flexible infrastructure models.

AI adoption creates a skills requirement

The AI push is also raising a more immediate question for enterprises and the wider technology ecosystem — whether the workforce has the skills needed to build and support these technologies.

Dell used the forum to highlight uDaan: Empowering India’s Future Workforce, a national programme that aims to prepare 23,000 young people for technology roles across AI, cloud and electronics manufacturing. The initiative brings together Dell, FITT-IIT Delhi, Learning Links Foundation and Generation India Foundation, with each organisation contributing to different parts of the skilling and employment process.

The programme will work with 100 ITIs and 90 higher education institutes across Delhi NCR, Bengaluru, Hyderabad, Chennai and Pune. Four curricula are being developed around AI application development, cloud development, assembly line operations and field technician roles, with input from more than 40 employers across technology, electronics manufacturing, global capability centres and hyperscalers.

The emphasis on employer participation is significant. Rather than stopping at training, uDaan is designed to connect students with employment opportunities, apprenticeships and entrepreneurship pathways. Dell is also committing more than 2,000 hours of employee mentorship as part of the programme.

“India's AI economy is creating roles faster than employers are able to fill them, and those roles require new skillsets,” Manish Gupta, president and managing director, Dell Technologies India, said.

Gupta positioned skilling as an important part of AI adoption, with Dell looking to build pathways that connect education more directly with industry requirements and employment.

For the technology ecosystem, that connection matters as AI adoption expands. Enterprises will need people who can develop AI applications, build and manage cloud environments, operate technology infrastructure and support the hardware behind these systems. The demand for these capabilities is likely to extend beyond traditional technology roles as AI becomes part of business operations.