India’s AI ecosystem prioritises the application layer, with around 80 per cent of funding concentrated in this space. Infrastructure and foundational AI account for roughly 10 per cent of the funding, according to a report released by early-stage VC firm SenseAI Ventures.
This is in stark contrast to the US, where foundational AI and infrastructure dominate, accounting for nearly 85 per cent of funding, the report noted.
“India is well positioned in the AI ecosystem. Our focus on applications is a feature, not a bug. There is too much focus in the media on foundational models and why we are not building them or investing in R&D. There is enough R&D happening at the application layer. It is applied R&D,” says Rahul Aggarwala, Managing Partner at SenseAI Ventures.
1 April 2026
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One reason for this focus on applications is that they offer faster return on investment (ROI) with significantly lower capital requirements, whereas foundational AI requires far higher investment and longer timelines.
“With limited domestic compute infrastructure at the application layer and a much smaller VC ecosystem compared to the US, founders are building lightweight, applied layers on top of global models,” the report titled 'State of AI' adds. Overall AI investment in India increased from $0.9 billion in 2024 to $2.5 billion in 2025.
Enterprises Lead the Way
In terms of the problems Indian founders are choosing to solve, around 25.5% are focused on enterprise solutions, which leads the way, followed by fintech at 13.3%. Speaking about this trend, Aggarwala says that the main reason is proof of ROI. Enterprise leaders have seen AI work, either within their own organisations or through industry networks. The study is based on a sample size of 1,200+ AI startups across India.
“The return on investment is significant, which is why enterprise spending on AI is rising. That said, while enterprise will remain a large segment, consumer AI is still underdeveloped and has significant room to grow,” he adds.
However, at present, we do not see many consumer AI startups in India. Aggarwala says this is because business models in consumer AI are still in flux. “We don’t yet have standout success stories in consumer AI, but that could change by 2026. Once a few successful examples emerge, they will drive more activity, just like Flipkart did for e-commerce,” he adds.
AI Shortens the “Time-to-Obsolescence”
A key breakthrough in the AI space is that startups are now able to generate revenue much faster than traditional SaaS companies. “A 10-person team can now threaten a $10B incumbent in under 18 months,” the report notes.
“There are three key factors. First, there is a strong top-down push from enterprises to adopt AI. Second, post-adoption results have been excellent. Companies are seeing real ROI, which drives further adoption. Third, AI has moved from experimentation to becoming a line item in enterprise budgets. This shift is accelerating revenue growth,” explains Aggarwala.
However, this rapid buildout is also creating significant constraints. “These constraints are largely physical, such as electricity, memory chips, and GPUs, and will take time to resolve,” the report adds.
