E-Paper
AI in the Global South’s Decade
This article is authored by Sabarish Chandrasekaran, CEO & co-founder, MediSim VR and Mukesh Kestwal, chief innovation officer, IIT Ropar (i-Hub-AWaDH).
As the India AI Impact Summit 2026 begins in New Delhi, it does so at a pivotal moment. For the first time, a global AI summit of this scale is being hosted in the Global South. This is not symbolic positioning. It reflects a structural shift in how artificial intelligence will be debated, governed, and deployed in the coming decade.
India’s AI strategy is anchored in the government of India’s vision of democratising technology. The ambition is clear: AI must not remain confined to elite laboratories or multinational platforms. It must be distributed, accessible, and productive for citizens, enterprises, and institutions across the country.
The global data supports India’s momentum. The Stanford Global AI Vibrancy 2025 report ranks India third in the world for AI competitiveness and ecosystem vibrancy. India is also the second largest contributor to GitHub AI projects, a powerful signal of developer energy and open innovation culture. This combination of scale, talent, and entrepreneurial intensity positions India uniquely in the global AI race.
The launch of the IndiaAI Mission in March 2024 with an outlay of ₹10,372 crore marked a decisive policy inflection. In less than 24 months, the mission has built foundational infrastructure. More than 38,000 GPUs have been onboarded for a common compute facility, enabling Indian start ups and academia to access affordable computational power. Twelve teams have been shortlisted to develop indigenous foundational models and large language models. Thirty applications have been approved for India specific AI solutions. Over 8,000 undergraduate students, 5,000 postgraduates, and 500 PhD scholars are being supported for talent development. Twenty-seven India Data and AI Labs have been established and 543 more identified.
These are not incremental steps. They represent a systematic attempt to build compute, capability, and human capital in parallel.
Private capital has responded. According to the Stanford AI Index Report 2025, India’s cumulative private investment in AI between 2013 and 2024 has reached approximately 11.1 billion dollars. Google has announced a $ 15 billion investment to establish an AI Hub in Visakhapatnam, its largest investment in India to date. The Tata Group has committed $ 11 billion to build an AI innovation city in Maharashtra. Under the IndiaAI Mission framework, multiple private enterprises are co investing alongside government to deepen the ecosystem.
This convergence of public investment and private capital is precisely what determines long term technological sovereignty. AI leadership is not achieved through policy declarations or venture capital enthusiasm alone. It requires alignment across compute infrastructure, foundational research, application ecosystems, talent pipelines, and regulatory clarity.
India has made an impressive start. But the next phase will demand sharper strategic calibration.
First, speed and direction must be synchronized. India cannot afford either reckless acceleration or bureaucratic hesitation. Development and deployment must occur at the right speed in the right direction. In high impact sectors such as health care, agriculture, financial inclusion, and public service delivery, AI deployment must be accompanied by domain validation, ethical guardrails, and measurable outcome benchmarks.
Second, India needs a coherent AI standards architecture. While India is actively shaping the global debate on AI development, usage, and safety, and has been the founder chair of the Global Partnership on Artificial Intelligence, domestic standardization remains fragmented. There is an urgent need to establish national AI standards covering model evaluation, bias audits, safety testing, explainability thresholds, and sector specific deployment norms. These standards should be interoperable with global frameworks but rooted in India’s socio-economic context. Without this layer, India risks scale without assurance.
Third, public compute infrastructure must be matched with high quality datasets. The 38,000 GPUs and common compute facility are transformative. But foundational models are only as strong as the diversity, cleanliness, and representativeness of training data. A structured national data governance framework that enables anonymized, consent driven, secure data sharing across public institutions will be critical.
Fourth, talent development must evolve from volume to depth. Through IndiaAI FutureSkills, support is being extended to 500 PhD fellows, 5,000 postgraduates, and 8,000 undergraduates. Two hundred ninety fellowships have already been awarded. Twenty-seven IndiaAI Data and AI Labs are operational in Tier 2 and Tier 3 cities, and 543 ITIs and polytechnics have been approved for expansion. FutureSkills Prime, a joint initiative of MeitY and NASSCOM, has seen more than 26.2 lakh candidates register, with over 16.65 lakh enrolled and trained in emerging technologies including AI, big data, IoT, cybersecurity, blockchain, and AR VR. These numbers are impressive. The next step is ensuring that this talent is absorbed into deep tech product ecosystems rather than low value repetitive tasks.
The intersection of AI and immersive technologies such as virtual reality illustrates both promise and caution. In medical education and healthcare training, AI driven simulation and VR based immersive modules are already reshaping learning models. They allow scalable, repeatable, risk free training for clinical decision making, surgical simulations, and emergency response. In a country where faculty shortages and uneven clinical exposure remain structural challenges, AI and VR can dramatically expand capacity. Yet here too, development and deployment must be aligned with accreditation standards, evidence-based validation, and ethical oversight. Without clear regulatory frameworks and clinical validation protocols, innovation may outpace trust.
India’s opportunity is historic. Hosting the India AI Impact Summit 2026 signals that the center of gravity in AI discourse is expanding beyond traditional power blocs. But to translate vibrancy into leadership, India must move from ecosystem building to systems thinking.
A strategic framework for the next five years should rest on five pillars. Compute sovereignty anchored in public infrastructure and indigenous chip roadmaps. Foundational model development aligned with Indian languages and sector specific needs. Robust AI standards and safety evaluation mechanisms. Deep integration of AI into priority sectors such as healthcare, education, agriculture, manufacturing, and climate resilience. And globally interoperable but locally grounded governance norms.
India does not need to replicate the AI trajectories of the US or China. It must define its own pathway, rooted in democratic values, developmental priorities, and technological ambition. The world is watching how the Global South shapes the AI century. With calibrated public investment, disciplined private capital, rigorous standards, and inclusive deployment, India can do more than participate in the AI race. It can redefine its direction.
This article is authored by Sabarish Chandrasekaran, CEO & co-founder, MediSim VR and Mukesh Kestwal, chief innovation officer, IIT Ropar (i-Hub-AWaDH).
