Funding resilience: India’s pathway lies in data and technology

October 13, 2025 - the International Day for Disaster Risk Reduction - marked a symbolic and strategic inflection point for India's resilience agenda. On this day, the Hon'ble Prime Minister inaugurated two state-of-the-art High Performance Computing (HPC) systems - 'Arka' at the Indian Institute of Tropical Meteorology (IITM), Pune, and 'Arunika' at the National Centre for Medium Range Weather Forecasting (NCMRWF), Noida. Together, these systems represent one of the most powerful meteorological computing capacities in the Global South.

The inauguration coincided with the G20 Working Group (WG) on Disaster Risk Reduction Ministerial Meeting in South Africa, which underscored the global need for technology-intensive and data-driven approaches to disaster resilience. India's actions, therefore, do not stand alone-they signal a new paradigm where investment in data and technology becomes synonymous with investment in safety, livelihoods, and long-term climate security.

The convergence of these developments highlights a global recognition that disaster risk reduction (DRR) in the 21st century is inseparable from digital transformation. The Sendai Framework for Disaster Risk Reduction 2015-2030, already approaching its final phase, calls for enhanced access to multi-hazard early warning systems and risk information for all by 2027. Yet for many developing economies, gaps in observational networks, computing capacity, and localized analytics have constrained progress. India, long a champion of South-South cooperation, is now demonstrating how strategic investments in scientific infrastructure and artificial intelligence (AI) can fill those gaps.

Bridging the data divide

For years, India's early warning ecosystem operated within severe structural limitations. Sparse Doppler radar coverage, inadequate sensor density, and fragmented data-sharing frameworks left vast regions under-observed.

The forecasting models, while scientifically robust, often ran on coarse grids of 12 kilometers or more, thus missing the micro-scale phenomena that trigger flash floods, heatwaves, or landslides. Computational constraints of limited available power (6-8 petaflops) further restricted the ability to run multiple models or AI-driven corrections at the speed needed for real-time decision-making.

This data and computational deficit translated into a resilience deficit. Disaster preparedness depended more on administrative experience than predictive intelligence - and although India's meteorological institutions delivered remarkable improvements in cyclone forecasting and monsoon prediction, AI pilots existed in research silos, unlinked from operational systems or local decision loops.

A technological turning point

The inauguration of Arka and Arunika changes that calculus. Together offering over double the previous computing power (now at over 20 petaflops) and high levels of storage (over 50 petabytes), they form the computational backbone for India's new Bharat Forecasting System (BFS)-a high-resolution, indigenously-developed model capable of six-kilometer grids and improved monsoon accuracy by over 30 percent. This leap in capacity is not merely technical-it is strategic. It enables the fusion of physical models with AI and machine learning algorithms to correct biases, predict extreme events, and produce impact-based forecasts at the village level.

Complementing this hardware revolution is Mission Mausam, a multi-year national initiative expanding observational coverage through radar, automatic weather stations, and integrated satellite-ground data systems. By densifying India's data grid, Mission Mausam ensures that AI models have the inputs they need to capture local variability, while the BFS provides the baseline physics-informed model outputs to train upon.

AI and the IndiaAI Framework: from innovation to implementation

Parallel to these scientific investments, India's AI governance architecture is maturing. With the goal of 'AI for All,' the IndiaAI Mission is led by the Ministry of Electronics and Information Technology (MeitY) and the public policy think tank NITI Aayog to ensure more people have access to data, computing, and algorithmic innovation. Through open data platforms and shared AI infrastructure, it lays the groundwork for translating meteorological and environmental datasets into public-good applications. The emphasis on ethical AI, responsible data use, and native capacity aligns perfectly with the needs of disaster risk reduction, where transparency, interpretability, and trust are as critical as accuracy.

Together, the BFS, Mission Mausam, and IndiaAI initiatives represent a systemic reconfiguration: from siloed forecasting toward an integrated, AI-augmented resilience ecosystem. This ecosystem can enable hyperlocal early warnings, anticipate cascading risks, and tailor communication to linguistic and cultural contexts-addressing the long-standing challenge of last-mile outreach.

Funding resilience through technology

The global discourse on climate and disaster resilience is shifting from response funding to resilience investment. The G20 WG DRR Ministerial in South Africa this year highlighted that the next frontier of resilience financing lies in data systems and technology platforms. India's leadership in building public digital infrastructure-whether through the Aadhaar biometric ID system, Unified Payments Interface (UPI),, or Covid Vaccine Intelligence Network (CoWIN)-has already proven how scalable data architectures can deliver social outcomes. Applying this philosophy to resilience means channeling resources into the invisible infrastructure that makes early warnings possible: sensors, computational capacity, models, and communication networks.

Each rupee invested in these data systems yields exponential social returns: reduced disaster losses, improved agricultural productivity, and strengthened trust in state capacity. By aligning AI and HPC investments with climate finance frameworks, India can also attract blended finance and private participation-transforming resilience from a cost center into a strategic growth investment.

Challenges and safeguards

Yet, realizing this vision requires careful navigation. Data interoperability and the ability to accurately interpret data that is exchanged between different agencies remains uneven; AI adoption in public institutions must overcome capacity and trust gaps. Ethical considerations-especially around privacy, accountability, and algorithmic bias-need continuous oversight. Moreover, the last-mile communication challenge persists: the most vulnerable often remain disconnected from digital warning systems.To close the information gap, we need a mixed approach. This means using high-tech methods like online alerts along with local resources like community radio, local volunteers, and communication in people's own languages.

A national framework for 'AI for Resilience'-anchored in the Sendai priorities and aligned with IndiaAI-can institutionalize safeguards while encouraging innovation. This should include transparent data-sharing protocols, explainable AI modules, dedicated funding for retraining and maintenance of models, and continuous human oversight.

The road ahead: toward AI-enabled public good

In practical terms, India can chart a phased roadmap for AI-driven resilience:

• pilot integration of BFS-AI systems in high-risk districts;
• expansion to sectoral applications (agriculture, health, water); and
• eventual national roll-out tied to the IndiaAI and Digital India frameworks.

Internationally, India's experience can serve as a template for other developing nations-an exemplar of how to align data, technology, and governance for human security.

The message emerging from October 2025 is clear: building resilience today requires funding not only relief but also research, data, and digital capacity. India's investments in HPC, AI, and forecasting mark a pivot from reactive disaster management to proactive, anticipatory governance-a model that could shape the global discourse on technology and resilience for years to come.

India's technological path to global resilience

As the world confronts accelerating climate volatility, India's example demonstrates that resilience is no longer the domain of emergency managers alone - it is a collective technological enterprise. By funding data infrastructure and AI ecosystems, India is redefining what it means to protect lives and livelihoods in the age of uncertainty. This alignment of vision, science, and statecraft may well become India's most enduring contribution to the global resilience architecture.

Dr. Sanjay K. Srivastava has over 25 years of experience in disaster risk reduction and climate change adaptation across India, South Asia, and the Asia-Pacific. He has worked with national governments, regional bodies such as SAARC, and international organisations, including the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP). He is now Chair Professor at the National Institute of Advanced Studies, Indian Institute of Science Campus, Bengaluru.