India is on the verge of a significant technological shift. With the entire world marking the beginning of the AI era, India with its huge reservoir of engineers, multi-lingual users, and data scientists is the winner at the large-scale. However, one drawback that India has had for a long time is the migration of skilled workers to other countries. As per the estimates provided by the industry about 15 % of the world’s AI talent comes from India but still, a lot of this talent gets absorbed in other countries.

India as the AI Moment

In the global competition of creating next-gen intelligence, India makes a compelling argument. One thing is for sure: the collaboration of the government and private sector is working to develop local large-language-models (LLMs)—AI systems that can even compete with the great ones globally! But then India itself presents a very remarkable asset that is none other than the multilingual intelligence.

Therefore, not only will the Indian model eventually capture the markets across the world but also reach out to rural communities, local businesses, government programs, and the entire population, which is often neglected by the global monolingual models.

The Challenge: Why Talent Still Leaves

Despite its potential, India is gradually losing its own talent. The first reason is that many Indian AI experts leave the country for better salaries, research facilities, global exposure, and clearer career paths.

• There is often a disconnect between Indian academia and industry: there is strong research but the connection to cutting-edge commercial AI and deep-tech-startups is weak.

• In advanced AI research, public funding in India is still majorly modest compared with that in the top global labs.

• Most of the Indian AI experts are transferred to global outsourcing or services roles instead of doing core research or working on product innovation.

• A venture capitalist observes: “India's tech talent pool is one of the biggest assets, but more and more talent is leaving for better returns.” He suggests that India not only needs to build an AI ecosystem but also to have the talent at the top-rung actively retained and rewarded; otherwise, it will be just a promise—the promise of leadership.

What India Must Do Now 

To move from being a mere supplier of talent to an AI innovation center, India needs to take fast actions on many fronts.

1. Fund AI Research Broadly 

Set up artificial intelligence centers of excellence not only in large metropolitan areas but in Figure-2 and Figure-3 cities as well. Promote interdisciplinary research—AI plus linguistics, AI plus social sciences, AI plus local businesses applying the technology.

2. Make Staying Attractive 

Apart from the infrastructure, India has to make top researchers stay with the country. It has to be through fellowships, competitive salaries (comparable to global labs), PhDs having industry linkages, incentives for researchers returning, and career segregation that blends research and product development.

3. Support Deep-Tech Startups 

Investments into AI-startups that deal with local problems in a large way should be encouraged: bilingual chatbots for rural sellers, AI for India’s healthcare, and agriculture-AI adapted to the local conditions. These startups provide talent an opportunity to create relevant products in the country instead of just offering services.

4. Build International Linkages 

Ask Indian-origin researchers settled abroad to take part in national projects (even from a distance). Collaborate with the best global AI labs. Establish exchange programs. This will not only bring back the know-how but also increase India’s global AI status.

5. Showcase India’s Ambition 

India’s economy is advancing towards a future worth $10 trillion. In the words of Khare, “This implies the opportunities offered here will be globally competitive.” Platforms like the 2026 Global AI Summit can be a means for India to proclaim its intent to lead—not to follow.

India's Multilingual Asset

Global AI models are usually having problems with language diversity, cultural context and local usability. The largest advantage of India probably lies here. An Indian-made AI that is able to not just communicate in Hindi but also Tamil, Bengali, Marathi, Punjabi—grammatically and culturally as well—can bring about real change.

• It can cater to local businesses in local languages.

• It can assist government initiatives and rural populations who do not know English.

• It can facilitate multilingual education, local language voice assistants, and inclusive AI that connects people with technology.

Thus, AI is not just a commercial product—but a development tool. And Indian talent is not just relevant—but essential to solving global problems in new ways.

The Stakes and the Win-Win Scenario

India is no more just a global tech labour supplier—it is well on its way to becoming an AI giant, given that it retains its talent within the country. 

What was once viewed as an inevitable consequence—brain-drain—now appears to be a policy and ecosystem failure that can be corrected. 

India has to deepen its investments in intellect, recognize the courage of innovators, and organize the environment in which innovation flourishes—not on a different soil or in another country, but right here. 

To paraphrase Rajat Khare, “The government has been very encouraging with AI.... However, the ultimate challenge will be how successfully we can keep and develop our talent. That will determine whether we are at the forefront or playing catch-up.”

Source: https://www.businesstoday.in/impact-feature/story/rajat-khare-believes-india-can-lead-the-worlds-ai-revolution-by-just-stopping-brain-drain-478096-2025-05-28

FAQs (Frequently Asked Questions)

Q1. Why is brain-drain so important for India’s AI ambitions? 

Because India is high on the list of producing engineering talent but the majority of it is either working abroad or in outsourced positions. The country aims to have the talent stay with it and thus help to build and innovate AI, not just as a provider of such services but as a global competitor with its models and deep-tech products. 

Q2. Will India compete with global AI labs like OpenAI or Google’s AI division? 

India may not exactly replicate them, but the power is in the doing different: model for the local languages, scaling the regional use-cases, combining global ambitions with local relevance. If the infrastructure is built—talent retained—India’s AI leadership will be a plausible scenario.

Q3. Which startups should India concentrate on to keep AI talent? 

Startups that tackle problems both locally and globally: healthcare, agriculture, and education with AI in local languages; voice assistants in English and other regional languages; AI for local industry automation; multispectral customer-service bots; and deep-tech research in NLP for Indian languages.

Q4. How can academia and industry collaborate better in India? 

By inventing joint research programmes, industry-supported laboratories in universities, PhD programmes connected with the startup product-goals, and creating career paths where researchers can shift back and forth between university and product roles in startups.

Q5. What steps can the government take to lure the AI talent in India? 

Giving fellowships and grants to the finest researchers; ensuring that the pay is competitive; investing in infrastructure like GPU clusters and LLM training centers; revamping the proficiency transfer of talent programs; offering tax incentives for deep-tech investments; facilitating the establishment of global partnerships and exchange programs.