Panelists in this video:
[•] Kiran Naik, CIO & CDO, JSW Infrastructure Ltd. (Moderator)
[•] Pushpender Bhardwaj, Head – IT Services & Infra Projects, Uno Minda
[•] Shobit Agarwal, Director – AI, ML & Data Engineer, Mastercard India
[•] Anurag Goel, Group Assistant VP, Digital Innovation & Information Technology, Aditya Birla Group
[•] Vinay H.P, Director IT Business, Rittal Private Ltd.
[•] Gautam Bakhru, Vice President – Data Center Services, Sify Infinit Spaces Ltd
Key Highlights:
[1] Gautam Bakhru, Vice President – Data Center Services, Sify Infinit Spaces Ltd:
+ AI is no longer constrained by software alone. It is increasingly constrained by compute capacity and power — which means business leaders and technology leaders must work together to ensure the infrastructure is ready before the AI workload arrives.
[2] Vinay H.P, Director IT Business, Rittal Private Ltd.:
+ AI infrastructure has to evolve rapidly. It is not enough to deploy GPUs; the entire data-centre ecosystem — power, cooling, networking and compute — must be redesigned to support AI workloads at scale.
[3] Shobit Agarwal, Director – AI, ML & Data Engineer, Mastercard India:
+ AI readiness is not just about buying GPUs or moving to the cloud; it is about rebuilding the underlying infrastructure — power, cooling, data centres and networks — to support AI workloads at scale. That is the strategic takeaway.
[4] Anurag Goel, Group Assistant VP, Digital Innovation & Information Technology, Aditya Birla Group:
+ As manufacturing becomes more intelligent and data-intensive, we cannot move every piece of real-time data to the cloud. Edge AI becomes critical — not only to reduce token and data-transport costs, but to process the right data at the right place, at the right time.
[5] Kiran Naik, CIO & CDO, JSW Infrastructure Ltd.:
+ AI is only as powerful as the ecosystem behind it — the quality of the data, the strength of the network, and the infrastructure that enables it.
[6] Pushpender Bhardwaj, Head – IT Services & Infra Projects, Uno Minda:
+ India cannot future-proof its AI decade by investing only in AI tools; we must first build the digital backbone that allows those tools to perform at scale.
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