As India represents the largest future AI user base and a market that is still open to foreign technology. So, the strategy of American companies is to win India to control the next billion AI users. — Annu Kumari
The AI Summit 2026 presented a vision of India’s role in the global AI ecosystem. India’s AI ecosystem is robust in sectors such as healthcare, logistics, customer service and financial technology which are application layer innovation. India focuses on applications layer due to three structural reasons. First, lower capital requirements. Training frontier models costs higher while applications cost far less. Second, massive domestic market. India has 1.4 billion users, 700 million internet users and 22 plus languages. This creates demand for localized AI products. Third, talent structure India produces software engineers, data scientists and SaaS founders.
Table: Evolving AI ecosystem of India
Layer Current status in India
Infrastructure Mostly NVIDIA + hyperscalers
Compute cloud AWS / Google / Azure
Foundation models Emerging (Sarvam AI, AI4Bharat)
Frameworks Mostly global
Applications Strong Indian startup ecosystem
Source: Own compilation
Companies like Sarvam AI signal an effort to develop Indian-language AI models that better serve the country’s linguistic diversity. However, a relatively small number of global technology companies dominate the AI compute infrastructure, large-scale training frameworks and frontier model development in India. Therefore, the concept of sovereign AI becomes crucial for India. The sovereign AI means building AI capabilities that are locally developed, controlled and aligned with national interests. For India, sovereign AI would require progress in several areas: national AI compute infrastructure, Indian-language foundation models, trusted data governance frameworks, local AI semiconductor development, independent cloud and deployment platforms. At AI summit 2026, the initiatives presented by Jio, Google, NVIDIA, Microsoft, Meta, Sarvam AI and several startups indicate early steps in this direction, though substantial work remains.
At the AI Summit 2026, Reliance Jio demonstrated the architecture of India’s emerging AI ecosystem. Reliance Jio presented a vertically layered AI vision organized into six layers: AI-ready infrastructure; Elastic AI compute; Data assets; AI models; AI frameworks; and AI solutions. Jio displayed a strategy to embed AI into everyday Indian life through Jio AI Home, Jio Bharat IQ, Jio Shiksha, Jio Arogya AI, Jio Sanskriti, Creator AI and Jio Frames. This is similar to Alibaba Group or Tencent built ecosystems in China. Jio appears to be positioning itself as the domestic orchestrator of India’s AI ecosystem which combines telecom distribution, data assets, developer platforms and consumer applications. However, the deeper layers like advanced compute and hardware still depend on global suppliers. While the ambition of Jio is significant, the success of such a stack will depend on whether Jio can build or localize these deeper layers.
Google positioned itself as an enabler of AI development for India’s digital public infrastructure. It showed partnerships with startups, research institutions and organizations working across healthcare, digital commerce and entrepreneurship. So, it implies that local startups and public initiatives build applications, but much of the training, deployment and scaling occurs on global cloud infrastructure. From sovereign AI viewpoint, it raises questions about platform dependency as much of the AI infrastructure including cloud computing, training environments and foundational models remains tied to global platforms.
NVIDIA showcased a wide range of Indian startups building AI solutions in robotics, generative media, enterprise analytics and voice technologies. It demonstrated that NVIDIA’s GPU infrastructure supports a wide spectrum of AI innovation in India. Without domestic alternatives or large-scale national compute infrastructure, India’s AI ecosystem may remain reliant on external hardware providers. While training advanced AI models requires massive computational resources and the global supply of such hardware is concentrated among a few companies. Interestingly, Sarvam AI was also listed in the NVIDIA pavilion. So, when NVIDIA highlights a company like Sarvam AI, it indicates that “this company is building important AI models using our infrastructure.” For NVIDIA, companies like Sarvam are strategic because India will be one of the largest AI markets in the world. Every model trained means more GPU demand.
Thus, it can be concluded that India’s AI startup ecosystem is thriving at the application layer, but the underlying compute infrastructure remains globally controlled. India’s strength clearly lies in innovation at the application layer, where its software talent and large domestic market provide a strong advantage. Therefore, AI summit 2026 raises a central strategic question that can India move deeper into the foundational layers of AI? Building sovereign AI capabilities would require progress in large-scale national compute infrastructure, domestic semiconductor ecosystems, advanced AI research institutions, locally trained foundation models. These layers are capital-intensive and require long-term industrial strategy. When foundational technologies are externally controlled then application ecosystem might also remain structurally dependent.
The global digital economies tend to fall into two categories: platform builders vs platform users. Countries that control infrastructure, chips, operating systems and foundational technologies are platform builders. While countries that innovate on top of externally built technological foundations are Platform users. From this viewpoint, technological sovereignty lies primarily in the lower layers of the stack. The potential Indian strength is uncertain in foundation AI layers (chips, compute, core models) but strong in application layers (services, vertical solutions). As of now, India equals to application innovation layer while US tech companies equal to foundational AI layer. But the ecosystem (Jio, Sarvam, IndiaAI Mission) suggests India is trying to move deeper into the stack. Moreover, the strong presence of Meta, Microsoft, NVIDIA, Google and Reliance Jio in the same AI summit ecosystem actually signals something deeper than just technology partnerships. It reflects a geopolitical and economic competition around the future AI market. As India represents the largest future AI user base and a market that is still open to foreign technology. So, the strategy of American companies is to win India to control the next billion AI users.
