AI Startups, Take Note: Here’s What Investors In India Are Looking For

For AI startups operating in sensitive sectors such as healthcare, finance, or surveillance, regulatory literacy is essential.

By Roma Priya

India’s artificial intelligence (AI) startup ecosystem stands at a transformative inflection point. With a strong base of engineering talent, increasing enterprise adoption of automation, and growing investor interest, the environment is favourable for innovation. However, for founders navigating this space, it is essential to recognise that innovation alone does not suffice. Investors now expect a balanced combination of technological capability, commercial clarity, legal rigour, and demonstrable market readiness.

Investors today are not inclined to support products merely because they are technologically advanced, but those that make commercial sense. They are drawn to AI solutions that solve real problems and create measurable value. 

The China Effect

With China proving its capability in developing efficient and cheap large language models (LLMs), Investors now seek real value, whether in the form of operational efficiency, cost optimisation, or new revenue opportunities, which must be tangible. Possessing proprietary algorithms is not enough. Founders must provide evidence of their application across sectors and present repeatable use cases that indicate scalability. These elements help reduce uncertainty regarding product-market fit.

Legal preparedness is another critical consideration, often underestimated by early-stage startups. Ambiguity surrounding intellectual property (IP) rights and data protection can present serious obstacles during investor due diligence. In many cases, AI products are built using open-source datasets or through collaborations with research institutions, which complicates ownership. 

Startups that maintain clear documentation regarding the origin and licensing of their technology signal professionalism and enhance investor confidence. The Investors, at a time, also examine the structure and content of commercial contracts. Therefore, the agreements must address service levels, liability, and IP rights to assure investors of operational reliability.

Digital Personal Data Protection Act

Investors are also increasingly cautious about the potential misuse of AI, particularly in areas such as misinformation, deepfakes, and algorithmic bias etc. Founders must proactively address these concerns by embedding ethical safeguards into their AI, establishing clear governance frameworks, and demonstrating transparency around algorithmic decision-making.

The enactment of India’s Digital Personal Data Protection Act (DPDP Act, 2023) will enhance data compliance from “nice to have” to a necessary standard for data-driven businesses. AI companies must implement clear consent mechanisms, comprehensive privacy policies, and formalised agreements with third-party vendors. Demonstrating early commitment to responsible data practices not only fulfils regulatory obligations but also builds long-term investors’ and customers’ trust.

Structure Of Equity Ownership

Even at the pre-revenue stage, Investors look for evidence of monetisation, which can be in the form of limited pilot revenues. A validated business model, whether based on subscription fees, licensing, or usage-based pricing, is crucial. Startups that can show even modest revenue traction are better positioned to raise capital than those still in the purely R&D phase.

The structure of equity ownership is another key area. Poorly maintained capitalisation tables, unresolved founder splits, or the absence of employee stock option plans can complicate investment. Startups that present a clean and well-documented equity structure demonstrate their readiness for institutional funding and long-term planning.

Migration Of Talent

However, a wider structural concern is the continued migration of India’s top AI talent abroad. While the country produces highly capable engineers and researchers, many are absorbed by more mature ecosystems overseas. This brain drain creates a gap between the development of innovation and its commercial realisation within India. Unless the domestic ecosystem offers stronger incentives, including early-stage funding and supportive policy frameworks, this trend may limit India’s ability to retain and scale its innovations.

For AI startups operating in sensitive sectors such as healthcare, finance, or surveillance, regulatory literacy is essential. Demonstrating familiarity with the relevant frameworks of regulatory bodies such as, Ministry of Electronics and Information Technology, the Securities and Exchange Board of India (SEBI), the Reserve Bank of India (RBI), or the Ministry of Health reinforces a startup’s long-term viability.

Recent investments in ventures such as Sarvam AI, Hyperbots, and ContraVault AI underscore investor interest in the sector. These companies stand out not merely for their technological sophistication but for their commercial discipline and legal readiness.

India’s most investible AI startups in 2025 will not be defined solely by their innovation. They will distinguish themselves by their ability to integrate legal structure, commercial viability, and regulatory compliance into their core operations. Founders who understand this shift will be better positioned to attract capital and build enduring, impactful enterprises.

(The author is the Founder of Burgeon Law)

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