India’s AI Journey: From User Capital to Developer Powerhouse – A Call to Action

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AI Image by Uma Desu

India’s Role in the AI Revolution: Falling Behind or Strategically Positioned?

By Uma Desu, Author of "GenAI: The Two Trillion Dollar Opportunity"

I, Uma Desu have been following the reactions to Deepseek in Social media. India’s AI journey stands at a critical turning point. While the world races ahead in foundational AI, India risks becoming a mere user nation, dependent on foreign AI models like OpenAI’s GPT, Meta’s Llama, and Anthropic’s Claude. Despite having the capital, talent, and infrastructure, Indian IT companies refuse to invest in LLMs, citing high costs and uncertain returns.

However, DeepSeek has shattered this myth. With just $6 million, it has emerged as a serious competitor, proving that lean operations and research-driven innovation—not massive corporate resources—drive AI breakthroughs. India must learn from this model and act fast to reclaim its AI future.

DeepSeek’s Playbook: Lessons for India

1. DeepSeek Proves LLMs Are Not Expensive—India Just Lacks the Willpower

One of the biggest arguments Indian IT firms make against developing large language models (LLMs) is that it requires billions of dollars. But DeepSeek has proved that with just $5 million, a startup can create a competitive LLM.

For context, Indian IT giants like TCS, Infosys, and Wipro make billions in annual revenue, yet none have made a serious effort to build India’s own LLMs. Instead, they rely on Western models, locking Indian AI startups into an expensive dependency on foreign AI ecosystems.

2. DeepSeek’s Lean Approach vs. India’s Corporate Bureaucracy

DeepSeek operates like an AI research lab, run by PhD graduates and top Chinese researchers. Instead of bloated corporate structures, it follows an agile, innovation-first approach, prioritizing Artificial General Intelligence (AGI).

In contrast, Indian IT companies:
✅ Focus on short-term service revenue
❌ Avoid high-risk, high-reward AI research
❌ Invest in superficial certifications over deep AI capabilities

Lesson for India: AI innovation does not need large corporations—it needs focused research labs, academic institutions, and agile AI startups that can challenge global leaders.

3. DeepSeek’s AI Model Price War and Its Impact on India

DeepSeek-V2 triggered an AI price war in China, forcing Alibaba, Baidu, and Tencent to slash their LLM pricing by up to 97%. By making AI access cheaper, DeepSeek has empowered startups, researchers, and businesses to experiment and innovate faster.

Meanwhile, in India:
❌ There is no domestic competition to challenge American AI firms.
❌ Indian startups pay a premium for using OpenAI, Google, and Anthropic models.
❌ Without affordable Indian LLMs, AI adoption in healthcare, manufacturing, and small businesses remains limited.

Lesson for India: A homegrown LLM ecosystem is not optional—it’s critical for AI independence. The government must support Indian academia and MSMEs (Micro, Small & Medium Enterprises) in building low-cost, high-performance LLMs tailored for India’s needs.

Why Indian IT Companies Won’t Lead India’s AI Revolution

For too long, the Indian government has expected large IT firms to lead AI breakthroughs. This is a mistake.

They prioritize IT services over product innovation
- Unlike DeepSeek, Indian IT firms focus on outsourcing contracts rather than AI research.
They lack the agility of AI-first startups
- Large bureaucratic organizations cannot move as fast as research-driven teams.
They have conveyed their disinterest in investing in foundational AI
- Indian IT Companies Top Executives have repeatedly said that Indian IT Companies are system integrators, users rather than builders. They have said that India does not have any big advantage in building LLMs. Instead of funding core AI research, they are training their employees with clickthrough certifications that do not translate into real AI capabilities. Many lakhs have completed AI Courses but hardly few really understand AI.

Who should lead India’s AI future?
✅ Academia: AI research labs, IITs, and independent researchers.
✅ MSMEs & Startups: Small, agile AI companies with a focus on domain-specific innovation.
✅ Government Support: Strategic investments in public AI infrastructure, cloud computing, and foundational model development.

India’s AI revolution must be built from the ground up, not from IT service boardrooms.

My Contribution: Taking Action for India's AI Future

While industry giants debate and government policies remain slow-moving, I have taken concrete steps to empower India's AI ecosystem. I have 26 Years of Experience in the Intelligence Domain.

Training: Trained Over 4,400 Students & 750 Faculty in Generative AI

Focused on real-world AI applications rather than superficial certifications.
Created hands-on projects in VLSI GenAI, predictive maintenance, and AI-driven automation.

Outreach: Reached Over 15,000 Engineering College Students Across India, 8000 School Students

Promoted AI education beyond elite institutions, making knowledge accessible in Tier-2 & Tier-3 colleges.
Conducted workshops on building, fine-tuning, and deploying AI models for practical use cases.

Advocacy: Advocated for Industry Readiness & AI Product Development

Guided students & startups to create AI products, not just consume AI APIs.
Helped students secure high-paying AI jobs, proving that India has talent, but it needs the right opportunities.

AI Ecosystem: Pushing for India’s Own AI Ecosystem

Promoting initiatives that push India to create its own foundation models.
Encouraging startups to develop domestic LLMs to reduce dependency on American models.

I firmly believe that India’s AI future must be built, not bought. This is not just a vision—it’s the mission I work towards every day.

What India Must Do Now

If India wants to move beyond being an AI user and become a true AI power, it must:

✅ Fund and build India’s own LLMs

Without homegrown foundation models, Indian AI startups will always be dependent on expensive American alternatives.

✅ Prioritize R&D in AI and AGI

The focus should shift from IT services to AI research labs that can compete with global innovators like DeepSeek.

✅ Support AI price competition

Just like China’s AI price war, India must have multiple AI providers to bring down LLM costs and make AI affordable for startups and small businesses.

✅ Government should back MSMEs and academia, not just big IT firms

DeepSeek proved that AI innovation comes from research, not large corporations.
India must fund small, focused teams that can challenge OpenAI and Google, rather than waiting for Infosys or TCS to do it.