Summary:
India’s generative AI (GenAI) startup scene is growing rapidly in 2025, with a 3.7X jump in new startups making it the world’s second-largest GenAI hub. While global funding has reached $54 billion, India’s share remains modest at $990 million. Still, Indian startups are pivoting fast, focusing on real-world uses like vertical SaaS and regulated industries. However, issues like limited computer access, lack of partnerships, and talent shortages are slowing progress. The report calls for better infrastructure, funding, and policy support to unlock India’s full potential.
India’s generative AI (GenAI) startup ecosystem is growing faster than ever in 2025. Over the past year, the number of GenAI startups in India grew 3.7 times, reaching more than 890 companies. This makes India the second-largest GenAI hub in the world, just behind the United States.
Globally, GenAI startups have also seen major growth. The number of startups worldwide has increased 9 times in just two years, crossing 4,500 companies by mid-2025. Most of these are focused on building AI tools for specific industries, rather than general-purpose tools.
Funding Trends: Big Numbers, but Uneven Growth
Across the world, GenAI startups have raised a total of $54 billion by the first half of 2025. But nearly 88% of that money went to large, late-stage companies. This shows that investors are betting on established startups that already have enterprise customers.
In the US, big tech partnerships, powerful computing infrastructure, and deep-pocketed investors have helped drive this growth. However, the US is also seeing a slowdown in new startup formation, as it becomes harder for small companies to enter the market.
India, meanwhile, is seeing the opposite trend. The country saw a 3.7X rise in total GenAI startups, and application-focused startups alone grew 4X, now making up about 83% of the total GenAI ecosystem in India.
Startups Pivoting Fast
One of the biggest trends in India is pivoting. About 63% of Indian GenAI startups have changed their business model or focus in the last year. Many are shifting toward vertical SaaS or AI tools built for specific industries like finance, healthcare, or law.
These domain-focused startups are also the ones attracting the largest funding rounds. Still, India’s total GenAI funding was just $990 million by mid-2025, showing that Indian startups are still not getting the capital they need compared to global peers.
Smarter Tech, Slower Scale
Indian GenAI companies are catching up with global tech standards. Many are now building using autoregressive models similar to those powering tools like ChatGPT. Also, 79% of startups use proprietary customer data, and 45% are using synthetic data to improve performance.
However, there are key gaps. While 64% of founders are working on making their models more efficient, 58% don’t have a solid compute strategy. This means many startups are struggling to manage costs and run their AI models effectively.
Another major issue is partnerships. Even though enterprise interest in GenAI is rising, 30% of Indian startups say they have no active partnerships. The top concerns are legal issues around intellectual property (IP) and complex regulations.
Challenges Holding India Back
Despite the momentum, Indian GenAI startups are still held back by three key problems: lack of talent, expensive compute infrastructure, and risk-averse funding. Many early-stage companies can’t afford to take risks or invest in deep R&D, so they stay in low-complexity zones.
India’s Unique Edge and What It Needs Next
India has a chance to stand out globally by building tools for local languages, creating digital public infrastructure (DPI)-linked AI, and developing AI agents for specific jobs.
To truly lead, the report says India must take action now. Key recommendations include:
- Making compute power more affordable and accessible
- Supporting startups with long-term, patient capital
- Helping them scale through government and enterprise adoption
With the right support, India’s GenAI boom could shape not just the next few years but the future of global AI innovation.