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Why Most AI Startups in India Don't Succeed

Why Most AI Startups in India Don't Succeed

Entrepreneur13-06-2025
9 out of 10 startups don't make it, by the end of the first year, 20 per cent fail; by the fifth year, that number jumps to 50 per cent, and by the tenth, nearly 70 per cent are gone
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India's domestic AI market is projected to more than triple to $17 billion by 2027, positioning the country as one of the fastest-growing AI economies globally. This rapid acceleration is being fueled by rising enterprise tech investments, a thriving digital ecosystem, and a robust talent base. The country already boasts over 600,000 AI professionals—a number expected to double to 1.25 million by 2027.
India's startup ecosystem is keeping pace with over 4,500 AI startups, 40 per cent of which were launched in the last three years. The country is fostering innovation across sectors, from health-tech and agri-tech to logistics and fintech. Many of these ventures are focused on solving uniquely Indian challenges using AI, making them globally relevant, as per the BCG's recent report, India's AI Leap: BCG Perspective on Emerging Challengers.
India's startup ecosystem is keeping pace with more than 4,500 AI startups, 40 per cent launched in just the last three years. The country is fostering innovation across sectors, from healthtech and agritech to logistics and fintech. Many of these ventures are laser-focused on solving uniquely Indian challenges using AI, making their solutions globally relevant, as highlighted in BCG's recent report, India's AI Leap: BCG Perspective on Emerging Challengers.
All signs point to a tech transformation on the horizon. The next decade could bring mass adoption of AI across Indian industries—an adventure we're just beginning to witness. However, the road to scaling remains bumpy.
Despite the buzz, venture-backed startup failures remain alarmingly high. According to forge fusion.io, 9 out of 10 startups don't make it. By the end of the first year, 20 per cent fail; by the fifth year, that number jumps to 50 per cent, and by the tenth, nearly 70 per cent are gone.
Only 1 per cent ever become household names. And, for first-time founders, the success rate is just 18 per cent. These facts are not interesting for the growth of startup ecosystem.
So what's slowing India's AI dream?
A Steep Climb
"India is standing on the brink of an AI revolution, driven by a rich talent pool and increasing enterprise appetite for transformation. Yet, for many AI startups, the leap from innovation to scale remains steep," said Rishi Verma, Head – AI Centre of Excellence, FSS.
According to him, less than 20 per cent of AI startups in India transition from pilot to production due to bottlenecks like limited access to compute infrastructure, fragmented data ecosystems, and the complex demands of enterprise integration.
Even when there is a clear product-market fit, the cost of scaling is crushing.
"Training or fine-tuning advanced models is expensive. GPU hours add up quickly, and maintaining healthy margins becomes difficult, especially when clients expect free PoCs," explained Nitin Lahoti, Co-founder & Chief Sales Officer at Mobisoft Infotech.
Startups often spend months building unpaid proofs-of-concept, only for enterprises to back out or delay procurement due to budget shifts or internal friction.
Missing Pieces
"The policy runway is full of potholes," pointed out Shailesh Dhuri, CEO of Decimal Point Analytics.
He added that while India is the fastest-growing country in AI patent filings, it still lags far behind China and the U.S. in volume. The lack of defensible IP makes it harder for startups to raise capital at strong valuations. On top of that, seed capital is relatively accessible, but deep-tech ventures struggle with follow-on funding.
"Training even a mid-sized 7B parameter model costs USD 2–3 million in GPUs alone. Most Indian cheques top out at USD 2 million," he said.
India's compute infrastructure is also lagging. While the government's IndiaAI Mission has made strides, only around 15,000 GPUs are expected to be available in the short term far behind global standards.
Vernacular Gen-AI Lead Growth
Despite the hurdles, several segments are witnessing strong tailwinds. The Indian BFSI sector is projected to grow its AI investments at a CAGR of over 33 per cent till 2030.
"What excites me most is the evolving collaboration model between enterprises and AI startups," added Rishi Verma. "Over 65 per cent of Indian corporates are now co-developing AI solutions with startups. It's not just about outsourcing innovation, it's about co-authoring the future."
Nirmit Parikh, Co-founder and CEO at Apna, echoed a similar sentiment, highlighting a surge in AI-powered recruitment platforms and virtual assistants.
"The AI recruitment market in India was valued at USD 661.56 million in 2023 and is projected to reach USD 1,119.80 million by 2030. Meanwhile, the conversational AI market is expected to grow at a 25.1 per cent CAGR," he said.
Apna, for instance, has partnered with Google Cloud to scale AI-driven hiring and interview-prep solutions, helping users access real-time, on-demand support.
Gaurav Kachhawa, CPO at Gupshup, sees similar momentum in fintech, D2C, CPG, and even automotive sectors.
"Our Petromin AI Agent helps users get real-time car service support via WhatsApp during emergencies. It's these kinds of hyper-contextual, AI-driven experiences that are driving growth," he said.
Akhil Gupta, Co-founder and CPTO at NoBroker, believes agentic AI is a game changer, especially in high-touch sectors like healthcare, e-commerce, and BFSI.
"Businesses want intelligent, multilingual systems that can respond naturally, solve queries, and even anticipate intent. We're seeing strong demand for voice-first AI and sentiment analysis tools that go beyond automation to deliver strategic insights," he said.
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