The AI Global South ascendancy: India’s strategy for an inclusive AI future

By Dr Badri Narayanan Gopalakrishnan

The emergence of Artificial Intelligence (AI) has bifurcated the global technological landscape. On one side are the established giants of the Global North, wielding enormous computational power and setting the initial norms. On the other is the Global South, a collective of nations facing unique developmental challenges but possessing vast, untapped potential. It is into this pivotal moment that the India steps to lead a new, more inclusive AI future, rooted in the philosophy of Vasudhaiva Kutumbakam (the world is one family).

India’s foundational principles on AI leadership —People, Planet, and Progress— converted into concrete multilateral action define India’s comprehensive approach to leading the Global South. India’s philosophy, encapsulated in the vision of ‘AI for All’, is pragmatic and human-centric. India’s two flagship initiatives directly address the core challenges of the Compute Gap and Language Gap, which are common impediments to AI adoption across developing nations.

IndiaAI Mission

The IndiaAI Mission is a comprehensive, multi-pillar strategy launched to build a robust, indigenous AI ecosystem. It is the government’s direct response to the unequal distribution of high-end computing power, which is currently concentrated in the Global North.

• Democratizing Compute: The mission is deploying a large-scale AI computing infrastructure, with plans to procure and deploy tens of thousands of Graphics Processing Units (GPUs) through public-private partnerships. Crucially, this is designed to be a shared digital commons, offering subsidized access for startups and researchers to train large-scale Foundational Models, directly addressing the most significant barrier to AI adoption in the Global South: infrastructure access.
• Sovereign LLMs: It funds the IndiaAI Innovation Centre (IAIC) to support the development of homegrown Large Language Models (LLMs) and Multimodal Models (like the BharatGen AI model) that are culturally relevant and specialized for Indian domains.

Digital India Bhashini (Bhasha Interface for India) is a national language technology mission designed to bridge India’s profound language divide—a challenge replicated across linguistically diverse nations in the Global South.

• Multilingual AI Models: Bhashini uses AI/ML and Natural Language Processing (NLP) to develop and make available hundreds of open-source models that support all 22 scheduled Indian languages for real-time translation and speech-to-text.
• Voice-First Interface: It prioritizes a ‘Voice-First’ approach, allowing citizens, including those with low digital literacy, to interact with government services and applications using their native spoken language.
• South-South Cooperation: India has explicitly declared its intent to share Bhashini’s models and platform with other Global South nations, offering a template for digital inclusion that counters the Ethnocentrism and resource-intensive nature of Western AI models.

AI for real world

India’s AI strategy distinguishes itself by deploying technology not for speculative gain, but for measurable societal impact in critical sectors like healthcare and agriculture, which are central to the stability and progress of the Global South.

India uses AI to overcome the core challenge of its healthcare system: the massive doctor-to-patient ratio disparity and the lack of diagnostic infrastructure in rural areas.

• AI for Disease Elimination: The National Tuberculosis Elimination Programme (NTEP) is a global case study in AI for public health. Recognizing that TB remains a major public health challenge, state governments have deployed portable X-ray machines integrated with AI-driven Computer Automated Detection (CAD) software, such as Qure.ai’s qXR or DeepTek’s Genki.
• Speed and Accuracy: This technology allows health workers to conduct mass, rapid screening even in remote villages or temporary community camps (like the one documented in Thane district, Maharashtra). The AI analyzes the chest X-ray and flags ‘presumptive TB’ cases within minutes, often with an accuracy exceeding 95%. This early, on-the-spot detection is crucial, as studies have shown AI detecting cases—including asymptomatic ones—that were missed by human readers, allowing treatment to begin within days rather than weeks or months. This cost-saving, cost-effective intervention serves as a direct model for low-resource settings worldwide.

With over half of India’s population reliant on agriculture, AI is crucial for increasing yield, reducing waste, and mitigating climate risks—challenges shared by all agrarian economies in the Global South.

• Optimizing Scarce Resources: AI-driven Precision Farming utilizes data from drones, satellite imagery, and IoT sensors to monitor crop health, soil moisture, and nutrient levels in real-time. In water-scarce regions like Maharashtra, AI-based systems have helped farmers reduce water usage for water-intensive crops like sugarcane by up to 25% by precisely scheduling irrigation cycles.
• Predictive Risk Mitigation: The government and partners have developed Pest Risk Prediction APIs and other advisory services. By training AI models on decades of historical climate, soil, and pest data, these systems provide farmers with hyper-localized, actionable advice via simple mobile apps, enabling preemptive action against crop diseases and pest outbreaks. This not only boosts productivity (pilots in Telangana reported income doubled for chili farmers) but critically strengthens the financial and food security of smallholder farmers against the backdrop of an unpredictable climate.

India’s leadership is defined by an agile regulatory framework and concrete steps toward international cooperation.

• A Responsible, Agile Regulatory Blueprint: India has adopted a pragmatic, ‘pro-innovation’ and agile regulatory stance. It focuses on ‘Do No Harm’ guidelines and leverages its leadership of the Global Partnership on Artificial Intelligence (GPAI) to co-design governance principles. This flexible, ethical framework provides a vital template for developing nations who need to manage AI risks without strangling their own technological potential.
• Expanding Digital Diplomacy and Partnerships: India is actively integrating its AI success into its foreign policy, moving beyond dialogue to direct technological export. Through initiatives like the e-VidyaBharati and e-ArogyaBharati (e-VBAB) network and the establishment of an IIT campus in Zanzibar, Tanzania offering AI programs, India is building capacity and sharing its DPI stack directly with African and ASEAN partners. This effort is aimed at creating a non-dependent, globally inclusive AI ecosystem.

By focusing on inclusion, pragmatism, and human-centric governance, India is not just building its own AI future, but architecting a more equitable and impactful one for the entire Global South.

The author is the founder of Infinite Sum Modeling LLC and Fellow, NITI Aayog. Views are personal.