Funding Patterns and Analyzing the Role of Domestic Investors' Behavior in Indian Startups (Emerging Tech – GenAI)
Abstract
India’s startup ecosystem has undergone transformative growth, emerging as a global innovation hub driven by rapid technological advancements, government-led initiatives, and increased investor interest. This study investigates the evolving patterns of domestic investment in Indian startups, with a focused lens on the Emerging Technologies (EMERGING-TECH) - Artificial Intelligence (AI) & Artificial Intelligence Generative (GENAI) sectors. Historically reliant on foreign capital, the Indian startup funding landscape has shifted significantly since 2016, witnessing the rise of domestic investors—including high-net-worth individuals, angel networks, corporate venture arms, and family offices—who now play a strategic role in early and mid-stage
funding. Through comprehensive data analysis and time-series forecasting using ARIMA and Prophet models, this research identifies key trends in funding behavior, sectoral preferences, regional disparities, and stage-wise investment decisions. The study reveals that domestic investors are more risk-averse, preferring scalable ventures with shorter return cycles, and disproportionately fund startups in Tier 1 cities, leaving Tier 2 and Tier 3 regions undercapitalized. It also highlights a growing interest in AI-enabled startups, though tempered by knowledge asymmetry and technical skepticism among investors. The findings offer actionable insights for policymakers, startup founders, and ecosystem enablers by mapping capital flow
dynamics, identifying investment gaps, and recommending strategic interventions. By emphasizing the role of domestic capital in fostering self-reliance and innovation, the study contributes to the broader discourse on sustainable entrepreneurship in emerging markets like India.
Keywords: Domestic Investors, Emerging Technology (ET), Artificial Intelligence (AI), Generative AI (Gen AI), Startup Funding, Indian Startup Ecosystem .
