As AI adoption accelerates across India’s startup ecosystem, technology leaders are shifting focus from experimentation to execution. The challenge, in the face of India’s potential $126 Bn artificial intelligence market by 2030, now lies in scaling the workload while maintaining reliable infrastructure, predictable costs and robust data pipelines.
To facilitate candid discussions around these challenges, Inc42 and Oracle recently hosted the second edition of CTO Dinner in Gurugram, a closed-door gathering of senior technology leaders from India’s startup ecosystem. The event brought together more than 25 CTOs, founders and engineering leaders to exchange insights on building scalable AI systems, navigating infrastructure choices, and redefining technology leadership in the age of artificial intelligence.
The dinner saw participation from across sectors including, automotive marketplace, ecommerce enablement, edtech and ecommerce. The attendees included Aniruddh Jain, chief product and technology officer at Cars24; Ashish Kumar, VP of engineering at Shiprocket; Shubham Verma, director of business, product and growth at UpGrad; Vikram Shah, cofounder and CTO at Internshala; and Sushant Pandey, CPTO at Snapdeal and AceVector Group. There were also several senior engineering leaders from across the startup ecosystem.
The evening’s discussions centred on a key shift underway in the AI ecosystem. While early conversations focussed on model capabilities and GPU availability, leaders today are increasingly grappling with deeper infrastructure questions around data pipelines, cloud architecture, cost predictability and operational scalability.
Nitin Kaushik, director of cloud solution engineering at Oracle India, noted that many organisations misunderstand what truly drives successful AI adoption. “The first thing which every tech leader thinks about AI is that AI equals a particular model which will solve the problem. That’s not the truth. AI is a journey, and it starts with data. You need good data and enough data to build meaningful AI systems,” he said.
Data infrastructure often becomes the bottleneck in AI projects, he added. “Without robust pipelines to ingest, organise and access different types of data, even the most advanced models struggle to deliver real business outcomes.”
Rethinking AI Infra And Evolving CTO Playbook
The participants also discussed the misconception that scaling AI simply requires adding more GPUs. According to Kaushik, infrastructure decisions need to be far more nuanced.
“When we talk about infrastructure for AI, people often think AI equals GPUs. That’s not true. You can’t simply add more GPUs and expect problems to be solved. Organisations need to start small, use APIs and scale gradually with the right architecture and predictability in cost,” he noted.
The conversation also touched on how the CTO’s role is evolving as AI becomes more deeply embedded in products and operations. Kaushik observed that technology leaders are increasingly shifting from building systems to designing outcomes. “Earlier, many CTOs operated as chief builders, focussed on developing technology and shipping products. What we are seeing now is a shift towards CTOs becoming architects of outcomes, where technology decisions are closely tied to measurable business value,” he said.
The dinner created space for technology leaders to share their experiences – from managing AI workloads and optimising cloud costs to building secure and scalable data foundations. The evening highlighted a broader transition underway in the ecosystem – from experimentation to execution, reliability and long-term infrastructure strategy.
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