Investors Shift Focus in AI Startup Funding Amidst Evolving Landscape
Changing Dynamics in AI Investment
The realm of Artificial Intelligence (AI) is rapidly transforming, and investors are adapting their strategies accordingly. No longer are they solely drawn to compelling AI narratives; instead, they are conducting thorough due diligence that encompasses various factors including AI governance, data ownership, model efficacy, and cybersecurity. Despite a notable 58 percent increase in AI funding within India, the overall funding for startups has seen a significant decline of nearly 39 percent in 2025. Recent studies indicate that investors are increasingly focused on whether these startups are making a tangible impact and enhancing profitability.
Jeenendra Bhandari, Chairman of JITO Incubation & Innovation Foundation, emphasized that the scrutiny investors apply to startups has become more comprehensive and multidisciplinary. Beyond the traditional financial, legal, and compliance evaluations, there is now a heightened focus on technology, data, and governance risks. This means assessing the quality and ownership of training data, intellectual property rights, model performance, scalability, cybersecurity measures, regulatory compliance, and ethical AI usage.
Moreover, investors are prioritizing evidence of commercial traction, which includes customer references, revenue quality, unit economics, and the repeatability of business models. Founder diligence, cap-table assessments, related-party transaction reviews, litigation checks, and the startup's capacity to attract and retain technical talent are equally crucial. As AI adoption accelerates, investors are demanding greater transparency regarding both opportunities and risks before committing long-term investments.
Karan Bhatty, Founder of Millow, noted that investors supporting AI startups are adopting a more nuanced due diligence approach. AI companies often present claims that are challenging to verify through standard data rooms. While pitch decks, demo videos, or founder narratives may suggest potential, investors now require proof of product functionality, genuine customer adoption, sustainable revenue, and legitimate rights to the technology and data utilized. A robust due diligence framework today typically includes entity-level checks, founder diligence, statutory reviews, shareholding assessments, litigation searches, adverse media screenings, and compliance checks.
For AI startups, additional validations regarding products and intellectual property, customer and revenue authenticity, employee or market feedback, and data sourcing, privacy, and governance are becoming standard. Investors are increasingly seeking diligence that transcends legal and financial reviews, aiming for an independent investigation into the startup's business reality, including its founders, products, customers, revenue, and risk indicators. The goal is not to hinder investment decisions but to ensure that capital is allocated with enhanced visibility and minimized blind spots.