Introduction
I’ve been watching the AI startup story in India with a mix of pride and growing unease. I, Hemen Parekh hcp@recruitguru.com, have written about AI’s promise before (see my piece "Amazing AI") — but the recent trend of more than a hundred Indian AI founders shifting significant parts of their operations to the United States has made me reflect harder on what this means for founders, users and our ecosystem.
What am I referring to? Several reputable reports now put the number of Indian AI founders who have moved or are planning to move to the US at around 100 or more, driven largely by the pull of customers, capital and talent in places like the Bay Area and other US hubs [cite: Economic Times, Business Standard].
Why founders are moving
Funding landscape
- Larger, more specialised pools of capital: Many US investors are making bigger, earlier bets on AI infrastructure and deep research-heavy plays. For founders building infrastructure or large-model related businesses, the size and risk appetite of US funds can be decisive. Reports note that some founders say fundraising was easier after establishing a US presence [cite: Economic Times].
- Faster decision cycles: Founders frequently describe faster term sheets, quicker due diligence and a willingness to fund longer time horizons in the US versus more conservative or revenue-immediate expectations at some local investors.
Talent access
- Density of researchers and engineers: The Bay Area, certain East Coast hubs and other US centres still host dense networks of senior ML researchers, hardware specialists and MLops engineers. For teams building foundational models, that proximity matters for hiring, collaboration and serendipity.
- Hybrid team models are emerging: Many startups keep engineering or product teams in Bengaluru, Delhi-NCR or Mumbai while moving business, sales and research leadership closer to customers in the US. This hybrid model keeps costs down but increases the perceived need for a US foothold [cite: Economic Times].
Go-to-market and access to customers
- Enterprise buyers in the US are large, more willing to pay for AI solutions and often set standards that ripple globally. For AI products that target large enterprises or verticals where the biggest buyers are American, being local accelerates sales cycles and product-market fit.
- Market feedback loops are faster: Founders report that being in-market lets them iterate with early adopters, embed with pilot customers and close pilot-to-deal cycles more quickly.
Regulatory and business environment
- Compliance, procurement and procurement preferences: For some regulated verticals, US-based customers prefer contracts with entities in their jurisdiction. For startups aiming at those verticals, a US presence becomes a practical step.
- Immigration and legal frictions: Ironically, tougher visa environments and new policy proposals in the US have complicated moves for founders and talent — but many still find the move worthwhile because of the ecosystem advantages.
Implications for India
Brain drain vs diaspora benefits
- Brain drain risk: A sustained movement of early-stage founders and senior product or research leaders to the US can thin India’s domestic leadership pool, making it harder for the next cohort of startups to find mentors, early hires and role models.
- Diaspora benefits: Conversely, an engaged Indian founder community in the US can become a powerful diaspora — helping Indian teams hire, opening market doors for India-based product teams, and directing capital and attention back to India. The net outcome depends on the degree of continued engagement and intentional collaboration.
Funding ecosystem
- Short-term capital flight: When headquarters and cap tables move, more of the follow-on capital and exits may flow outside India, reducing local fund recycling.
- Signal to LPs and founders: If US VCs capture a disproportionate share of AI winners, Indian funds may need to adapt their sector expertise and check sizes to stay competitive.
Talent pipeline
- Retaining mid-career ML talent becomes harder if the most exciting research roles and product opportunities are perceived to be abroad.
- However, India’s large developer base and low-cost engineering strength remain advantages; hybrid models keep a significant part of product and R&D in Indian cities such as Bengaluru, Delhi-NCR and Mumbai.
Policy changes needed
- India needs targeted incentives for deep-tech R&D, clearer data-usage rules that support domestic innovation, and funding vehicles that can back longer-horizon, capital intensive infrastructure plays.
- Public sector procurement and demand-creation for AI in health, agriculture and public services can create large local use-cases that make building locally more attractive.
What Indian stakeholders can do
Policy recommendations
- Create mission-oriented R&D funds and tax incentives that make long-term AI research economically sensible to keep in India.
- Fast-track visas and researcher exchange programs that encourage two-way mobility — not just permanent relocation.
VC and community actions
- VCs must build deeper domain expertise in ML infrastructure, models and compute-intensive plays and be prepared for larger follow-on rounds.
- Syndication with US funds can let founders stay Indian while getting US market access; VC networks should formalise these pathways.
Talent retention strategies
- Make senior engineering and research roles more attractive through equity plans, meaningful ownership and opportunities to work on global-scale problems from India.
- Encourage hybrid career paths (e.g., multi-location leadership roles) so senior leaders split time rather than move permanently.
Collaboration models
- Hybrid R&D hubs: Indian engineering teams plus small research squads in the US give startups the best of both worlds.
- Joint labs and public-private partnerships: Indian institutes and industry should co-invest in labs that retain foundational research in India but collaborate internationally.
Conclusion
This moment is neither a simple “exodus” nor a final verdict on India’s AI ambitions. It’s a complex market response: founders chase customers and capital where the pull is strongest. The right response is not to wall off borders, but to build incentives, funding structures and talent pathways that make India an undeniable choice for the world’s next generation of AI companies.
If policymakers, investors and founders treat this trend as an early warning and an opportunity, we can convert transient relocations into durable partnerships — where Indian cities remain the engineering and innovation backbone while founders enjoy the market edge abroad. That balanced future is within reach, but it will take deliberate work from all of us.
Regards,
Hemen Parekh
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