How ready is India for its own Deepseek moment?

As China makes significant strides in artificial intelligence with Deepseek, the question arises: can India carve its own path in AI innovation? While India boasts a thriving tech ecosystem, a vast talent pool, and a growing startup culture, it also faces challenges like limited access to high-quality datasets and computing power. However, with strategic investments, policy support, and industry collaboration, India has the potential to develop homegrown AI tools that cater to its unique linguistic, economic, and societal needs. Could this be the moment for India to redefine its AI future?

Meher Patel, Founder of Hector, believes that India is at a pivotal moment in its AI journey. According to him, while China and the US have dominated AI research and large-scale deployments, India has the potential to carve out its own AI identity.

“Our strengths lie in a massive, tech-savvy workforce, a thriving startup ecosystem, and rapidly expanding digital infrastructure. However, challenges such as limited high-performance computing resources, fragmented AI research, and dependence on imported AI models need to be addressed,” Patel explains.

To have its own "DeepSeek moment," India must focus on:

• Building AI Infrastructure:Establishing large-scale AI computing capabilities, including indigenous GPUs and cloud platforms.
• Investing in R&D:Encouraging universities and startups to conduct foundational AI research with government-backed grants.
• Developing Open-Source AI Models:Creating AI systems trained on local datasets, reducing dependency on foreign technology.

If India can address these areas strategically, we have a real shot at building globally competitive AI solutions that cater to our unique needs, says Patel.

Abhinav Jain, Co-Founder and CEO, Almonds Ai, notes that India is at a fascinating crossroads when it comes to AI development.

“On one hand, we have this incredible advantage—a massive pool of tech talent and a fast-growing digital economy. On the other hand, we face specific challenges like fragmented data, infrastructure gaps, and, of course, catering to such a diverse population. But honestly, these challenges are also where the biggest opportunities lie. Take our diverse datasets, for example—they cover a wide range of languages, behaviours, and industries. That’s a goldmine for training AI models to be more adaptable and inclusive. And the scale—if you can build a solution that works in India, you can pretty much take it global. What excites me the most is the potential to solve real, on-the-ground problems. Whether it's improving financial inclusion, enhancing healthcare, or optimizing supply chains, there’s so much room for AI to make a tangible difference. The key is to stay grounded—building AI that’s not just technically advanced but also practical and accessible,” Jain explains.

Linguistic diversity

India’s linguistic diversity presents a unique opportunity to develop AI models tailored for regional languages, ensuring greater accessibility and inclusivity. By leveraging large-scale multilingual datasets, AI can be trained to understand local dialects, cultural nuances, and contextual meanings, making it more effective for India’s diverse population. By harnessing India’s linguistic richness, AI can bridge digital divides, empower local businesses, and enhance citizen services, making technology truly inclusive for all.

India’s language diversity is both a challenge and a huge opportunity, quips Abhinav Jain. With so many languages and dialects, you can’t rely on a one-size-fits-all approach.

According to him, the real game-changer is moving beyond basic translation. “AI needs to understand cultural nuances—how people express emotions, their intent, even things like humour, which can vary wildly across regions. For instance, how someone in Delhi interacts with a platform might be very different from someone in a rural area in Tamil Nadu. At Almonds Ai, we’re already exploring ways to make engagement platforms more inclusive—whether it’s supporting multilingual interfaces or training AI to personalize experiences based on cultural behaviors. And to be honest, it’s not just about inclusivity—it’s also good business. When you engage people in their own language, you build deeper connections and drive better outcomes,” he adds.

According to Meher Patel, India’s linguistic diversity is both a challenge and an opportunity for AI development. Unlike AI models trained primarily in English or Mandarin, India requires a multi-lingual approach to AI. The key to success lies in:

• Localized Data Collection:Developing extensive datasets across India’s 22 scheduled languages and numerous dialects to train AI models.
• Industry-Academia Collaboration:Partnering AI companies with linguistic research institutes to improve regional language processing.
• AI for Vernacular Internet:Advancing speech-to-text and text-to-speech solutions in Indian languages to enhance digital accessibility for millions.

Patel says that by investing in AI models that cater to India’s linguistic diversity, India can create technology that is more inclusive and drives higher adoption among users who are not fluent in English.

The government’s role in innovation

As AI reshapes industries worldwide, the Indian government has recognized its potential as a catalyst for economic growth and technological advancement. Through policy frameworks, funding initiatives, and strategic collaborations, the government is fostering an ecosystem that encourages AI research and development. Initiatives like the national programme on AI, responsible AI for youth are already paving the way for innovation, while investments in AI-driven startups and public-private partnerships are strengthening India’s position in the global AI race. But what more can be done to propel india toward AI leadership?

Meher Patel notes that the Indian government has taken significant steps to encourage AI innovation, but a more concentrated push is needed to match global leaders. Some of the key initiatives include:

• National AI Strategy (NITI Aayog):Promoting AI adoption in critical sectors like healthcare, agriculture, and education.
• India AI Mission:Establishing research roadmaps, AI innovation centers, and fostering public-private partnerships.
• PLI Schemes & Startup Grants:Offering incentives to AI startups and supporting domestic AI tech development.

To accelerate AI growth, the government should focus on:

Developing a strong AI regulatory framework that balances innovation with ethical concerns.

Boosting AI research funding, similar to China’s extensive investment strategy.

Integrating AI in governance to improve public services through automation and data-driven decision-making.

The Indian government has taken some positive steps toward promoting AI innovation, says Abhinav Jain.

“Initiatives like "IndiaAI" and "Digital India" are already laying the groundwork by encouraging research, setting up AI innovation hubs, and fostering public-private partnerships. The recent focus on AI in education, healthcare, and agriculture is particularly promising—it’s about using technology where it matters the most. The next big step is data access. For AI to truly thrive, we need open datasets—while, of course, maintaining privacy standards. Imagine what startups and researchers could achieve if they had better access to high-quality, diverse data—it would accelerate innovation like nothing else. Also, funding more AI-specific R&D and encouraging local talent through fellowship programs can play a transformative role. In short, a collaborative approach between the government, industry, and academia is crucial to ensure that India doesn’t just adopt AI but leads the next wave of innovation,” he adds.

The role of start-ups

How can Indian startups and researchers collaborate with established AI players and international experts to develop cutting-edge AI tools, while also ensuring that India's unique needs and strengths are addressed?

Collaboration is everything, says Abhinav Jain. No one can go alone, especially in a field like AI where things are moving so fast.

“Indian startups bring speed and innovation to the table, while established players offer scale and advanced research capabilities. Bridging these two worlds can unlock some really exciting possibilities. Open-source projects are a great example—they’re a powerful way to share knowledge and democratize innovation. Another area that’s often overlooked is cross-border collaboration. Partnering with international AI experts allows us to adopt global best practices while fine-tuning them for local needs. For example, the way we think about AI for rural communities or multilingual contexts can provide fresh insights that global players might overlook,” Jain adds.

Meher Patel says that collaboration is key to India’s AI growth. To bridge the gap with AI giants like the U.S. and China, Indian startups and researchers should explore:

• Public-Private Partnerships:Large corporations can mentor and fund AI startups to drive rapid innovation.
• Global AI Collaborations:Working with international AI research institutions to access the latest advancements and datasets.
• AI Talent Incubation:Strengthening AI education programs and accelerator initiatives to nurture India’s AI talent pool.

India is on the cusp of an AI revolution. By fostering partnerships, investing in infrastructure, and leveraging our unique strengths—such as linguistic diversity and a vibrant startup ecosystem—we can create AI solutions that are not just globally competitive but also tailored to our own needs.