AI Impact Summit 2026: Can India become a global AI superpower?

The AI Impact Summit 2026 in New Delhi was more than a global gathering. It was a declaration of intent. Prime Minister Narendra Modi outlined a bold ambition: to position India among the top three AI superpowers in the world. The message was clear. India must not remain a consumer of artificial intelligence. It must become a creator and exporter.

To understand what this ambition means for enterprises, startups and the broader AI ecosystem, we reached out to Satyendra Pasalapudi, Founder and CEO, Chat4ED Enterprise Solutions. As the founder of an artificial intelligence platform working at the intersection of technology and real-world deployment, his perspective bridges policy intent and enterprise execution.

What follows is his detailed analysis of the summit and India’s evolving AI strategy.

India’s AI superpower ambition and the USD 200 billion investment roadmap

At the AI Impact Summit in New Delhi, Prime Minister Narendra Modi laid out an ambitious vision for India’s technological future: positioning the country among the top three AI superpowers in the world. In an interview with ANI, he emphasised that India should not remain merely a consumer of artificial intelligence but emerge as a global creator and exporter of AI technologies. His vision includes Indian-built AI models serving billions of users worldwide in their native languages, fostering startups valued in the hundreds of billions of dollars, and generating millions of high-quality jobs.

To achieve this, India is targeting an estimated USD 200 billion in AI investments over the next two years, largely expected from the private sector. The investment strategy is built around strengthening what officials describe as a five-layer AI stack. The foundational layer is energy, as AI systems require vast amounts of reliable and increasingly clean electricity. Without sufficient power infrastructure, scaling AI is impossible. The second layer consists of data centres and network infrastructure, which serve as the backbone for storing and transmitting massive volumes of data through broadband and 5G networks.

The third layer is compute, particularly semiconductor chips that power AI training and deployment. These chips perform the heavy computational tasks required to run advanced AI models at scale. The fourth layer includes the AI models themselves, trained on large datasets to recognise patterns, generate outputs, and make predictions. Finally, the fifth layer involves applications, the end-user products such as chatbots, healthcare diagnostics, agricultural platforms, and language translation tools that integrate AI into everyday life.

Most of the USD 200 billion investment will go toward strengthening the bottom layers, energy, infrastructure, and computing, forming the foundation of India’s AI ecosystem. An additional USD 17 billion is expected to be directed toward deep-tech innovation and application development.

Global tech expansion and India’s role in AI development

Global technology companies are already expanding their footprint in India. OpenAI and Anthropic are increasing operations and forming partnerships with Indian firms. Anthropic has announced an office in Bengaluru and collaborations with companies like Infosys, Cognizant, and Air India to deploy AI tools and custom agents across industries such as telecom and financial services. Google and Meta are also expanding data centre capacity in India. This reflects a shift: global tech giants increasingly see India not just as a market, but as a strategic partner in AI development.

However, a key challenge remains localisation. Western AI models often lack customisation for India’s linguistic diversity, which includes 22 official languages and hundreds of dialects. Addressing this gap, Indian initiatives such as BharatGen, a government-backed program, are launching multilingual AI models like PAM-2. Another startup, Sarvam AI, backed by global investors, is developing AI models designed for Indian languages in both text and voice formats. These efforts aim to deliver affordable AI solutions for classrooms, clinics, and agricultural sectors.

Despite organisational challenges at the summit due to overwhelming attendance, India’s AI push signals a clear strategic intent: to build foundational infrastructure, encourage domestic innovation, and position itself as a global AI powerhouse.

Due to the overwhelming response and resulting protocol and security challenges, several industry leaders faced difficulties entering the venue and locating the appropriate halls. A more structured and organised approach is required, including clear demarcation, proper identification mechanisms, and dedicated entry lines for industry leaders.

Enterprise implications: Infrastructure first, applications next

From an enterprise standpoint, the five-layer AI stack offers clarity. It reminds organisations that applications sit at the top of a much deeper pyramid. Without reliable power, scalable data centre capacity and affordable compute, enterprise AI adoption will stall.

For CIOs and founders alike, the message is pragmatic. Invest in foundations first. Align with infrastructure build-out. Build localisation into design. Treat AI as an ecosystem play, not a standalone software purchase.

If India succeeds in building strong lower layers of energy, network and compute, application innovation will accelerate naturally. Startups will not need to struggle for expensive computing. Enterprises will not need to depend entirely on foreign infrastructure. And AI solutions tailored for Indian languages and sectors will become more viable.

The AI Impact Summit 2026 has set the direction. The ambition is large. The capital commitment is significant. The structural roadmap is defined.

The real test now lies in execution, coordination and disciplined infrastructure build-out. If India can align investment, talent and enterprise adoption around this five-layer AI stack, the ambition of becoming a global AI superpower may shift from aspiration to reality.