2 days ago
From Deal Sourcing to Exits: The AI Advantage in Venture Capital
In India, firms are doubling down on tech-led diligence and proprietary data-driven strategies. As AI adoption deepens, it promises to sharpen competitive edges, even as challenges around infrastructure and talent persist.
Opinions expressed by Entrepreneur contributors are their own.
You're reading Entrepreneur India, an international franchise of Entrepreneur Media.
Artificial Intelligence is fast becoming the next big disruptor in the venture capital landscape, not just as an investment theme but as a transformative internal tool. In India, firms are doubling down on tech-led diligence and proprietary data-driven strategies. As AI adoption deepens, it promises to sharpen competitive edges, even as challenges around infrastructure and talent persist.
According to a recent report by Gitnux, 42 per cent of VC firms globally use AI for deal sourcing, while 68 per cent of the firms believe that this technology will significantly improve investment decision accuracy. The report further stated that in deal sourcing and market research, proprietary deal-scanning tools and analytics platforms are adopted by 75 per cent of top-tier VC firms worldwide.
When it comes to due diligence, NLP-driven sentiment analysis is helping as much as 50 per cent of VCs assess market and founder cues in real-time. VCs also reported a 70 per cent improvement in portfolio-related operational efficiency using AI-backed dashboards and KPIs, according to data from Gitnux.
Rahul Agarwalla, Managing Partner, SenseAI, feels that what used to take weeks now only takes hours.
"AI has redefined the front end of our venture workflow, from deal sourcing to diligence, giving us unprecedented scale, speed, and precision. At SenseAI, our proprietary engine surfaces technical founders months before they raise, using a live signal graph of research papers, product launches, and social media activity. We run thematic market scans, generate automated investment briefs, and close transactions faster with NLP-powered agents," said Agarwalla.
AI is poised to be the next VC game-changer by enabling faster, data-driven decision making, with the technology helping firms filter a large number of startups more efficiently and spot leads earlier. AI can also help in faster, data-driven decision making by enabling NLP analyses of customer sentiment, founder profiles, and competitiveness.
The new-age technology can also help create value through talent and tech advisory a with commitments to "AI-first" theses and tech depth help VCs distinguish themselves from peers.
AI is proving to be more than just a vertical for investing, but is also reshaping the VC toolkit in India. As the adoption of this new-age technology accelerates, one can expect VC firms to increase hiring of AI talent, build proprietary analytics and deal-screening systems, and bolster infrastructure with partnerships and advocacy around AI.
While promising, challenges exist around GPU shortages and limited domestic LLMs that slow down scalable innovation. VC firms are still in the initial stages of the race to hire AI/ML professionals for internal processes.
Although AI helps us do things faster, venture is still a deeply human craft, and "Models can't assess founder resilience, ethical integrity, or long-term vision, only repeated human interaction can. AI gives us leverage; human judgment gives us conviction."
"The firms that get this balance right will define the next decade of venture capital. Venture capital is paid to underwrite non-linear futures. Deciding whether a novel idea can become a category-defining company is a deeply human endeavor rooted in taste, contrarian insight, imagination, and pattern-breaks that AI cannot model or predict," said Agarwalla.
While challenges remain, the fusion of national initiatives such as IndiaAI and VC-driven AI integration signals a transformative shift in how capital is deployed and value is generated. India's AI-powered VC evolution may very well define the next wave of startup success and potentially global exit narratives.
