India eyes global AI leadership with talent, domain expertise

India is preparing to capitalise on Artificial Intelligence (AI), aiming to translate its talent pool, entrepreneurial experience, and domain expertise into global AI leadership. According to NITI Aayog, AI could contribute $500–$600 billion to India’s GDP by 2035, driven by productivity gains and sector-specific innovations.

India qualified to lead

While India may have missed the initial race to develop Large Language Models (LLMs), business leaders speaking to The Federal on the sidelines of the CTOTalk 2025 Summit in Chennai said the country is well-positioned to lead in creating AI applications that solve real-world business challenges. Suresh Sambandam, founder and CEO of Kissflow, emphasised India’s strength in domain-specific AI.

“These agents handle specific tasks and work collectively to solve complex problems. India has the talent and domain knowledge to lead here,” he said.

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Demand for autonomous AI agents

The rise of agentic AI – autonomous systems capable of executing tasks with minimal human intervention – has accelerated adoption in India. Workplace AI usage surged from 46 per cent in 2024 to 77 per cent in 2025, while over 80 per cent of Indian companies are exploring autonomous AI agents, according to an Atlassian report.

The economic implications are significant. Sambandam highlighted the “salary gap” created by AI: automating routine tasks can drastically reduce staffing requirements, freeing resources to scale businesses.

“AI enabled us to cut our support team from 14 to 4, showing how one person can now manage operations that previously required a team,” he said.

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Budget still a challenge

Enterprise readiness, however, remains a challenge. Deepak Dastrala, CTO of Intellect AI, noted that most organisations have yet to commit large budgets to AI transformation due to gaps in people, processes, culture, and tooling. Sectors such as banking and financial services are particularly ripe for disruption, with 40–47 per cent of tech spending tied up in operational systems that could be reimagined with AI.

Data remains India's core advantage. Sreedhar Gade, head of AI and Cloud Engineering at Freshworks, cited logistics and pharmaceuticals as examples of domain-specific AI outperforming generic models.

“A logistics company with 65,000 trucks faces problems no off-the-shelf AI tool can fully solve. Domain-specific solutions predict and prevent issues, not just detect them,” he said.

Need to develop right talent

Sudheer Bandaru, CEO of Hivel, emphasised measurable outcomes. “LLMs may be commoditised, but forward-deployed engineering can deliver niche solutions that generate tangible business impact,” he said.

“If we focus on developing the right talent for this AI world, there’s so much more to come. The opportunity is massive, and India is ready,” Sambandam concluded.