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South and Southeast Asia are the climate hotspots. In the last two decades, over 750 million people in South Asia have been affected by floods, heatwaves, and cyclones, with India accounting for nearly 40% of these impacts (World Bank). Cities like Delhi and Dhaka are already experiencing wet-bulb temperatures at or near survival thresholds, while coastal areas face increasing salinity and storm surges.
The region’s resilience gap is not only about climate risks, but also digital and gender divides. Women in South Asia are 41% less likely than men to use mobile internet, contributing to 265 million fewer women online globally (GSMA, 2024). This matters because critical climate information—early warning systems, relief payments, agricultural advisories—is delivered digitally. Financial exclusion adds another layer: more than 700 million women worldwide remain outside formal financial systems (World Bank Global Findex), making it harder for them to receive emergency support or invest in adaptation.
Meanwhile, capital is beginning to move. Globally, funding for “AI for Good” has crossed USD 1 billion in 2024, with climate resilience one of the fastest-growing themes (Climate Change AI). The Bezos Earth Fund committed USD 100 million in 2025 to an AI for Climate and Nature Grand Challenge (Axios). Regionally, Google.org’s APAC Sustainability Seed Fund launched a USD 15 million portfolio in India and Asia (AVPN).
The opportunity is clear: AI can help communities adapt to climate change. But whether it narrows or deepens inequalities will depend on who designs, funds, and governs it.
Heat resilience in India: In Delhi, SEEDS India and Microsoft launched Sunny Lives, an AI model predicting indoor heat stress by combining satellite imagery and building characteristics. Instead of city-wide averages, this tool identifies vulnerable buildings and households, informing targeted interventions such as cool roof programs, shaded areas, and ward-level Heat Action Plans.
Climate-smart agriculture: The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) developed the Intelligent Systems Advisory Tool (iSAT), which delivers hyper-local climate and crop advisories through WhatsApp. Tested in Maharashtra, it is now part of India’s Monsoon Mission III and is positioned for replication across the Global South. Meanwhile, Wadhwani AI created CottonAce, a computer vision tool that helps farmers detect pink bollworm infestations in cotton crops, reducing pesticide use and yield losses. Its Krishi 24/7 platform monitors multilingual media sources to alert farmers and extension workers to emerging agricultural risks.
Women’s entrepreneurship in the Philippines: Women-owned micro and small businesses in remote islands are using AI-powered chatbots to create digital marketing content and receive instant technical advice. This has reduced content production time from hours to 10–20 minutes, helping women expand their reach and resilience in climate-sensitive coastal economies (Manila Standard).
Carbon markets in India: Varaha is deploying machine learning and remote sensing to monitor carbon sequestration projects with smallholder farmers. In 2025, Google Carbon Removal signed a contract with Varaha to purchase 100,000 tons of biochar-based credits, demonstrating AI’s role in verifying integrity and channeling global finance to rural communities (Google).
Indigenous governance in the Mekong: Open Development Mekong, led by the East-West Management Institute, is building indigenous data sovereignty frameworks. By ensuring communities have control over their climate and land-use data, the initiative seeks to prevent exploitation and create more equitable AI-enabled adaptation tools.
The ecosystem includes research institutes, nonprofits, startups, and women-led networks:
India is positioning itself as a leader in public-good AI. The IndiaAI Mission, launched in 2024 with an allocation of ₹10,372 crore, aims to create shared compute capacity, national datasets, and centers of excellence. Climate, agriculture, and disaster risk management are priority verticals (PIB). At the state level, the Odisha AI Policy 2025 became the first in India to explicitly align AI with disaster preparedness, agriculture, and energy transitions (Times of India).
In the ASEAN region, the AI Governance and Ethics Guide (2024–25) sets out principles for responsible AI deployment, aiming for interoperability and trust. This is especially relevant for disaster warning systems, agricultural advisories, and community-level applications (ASEAN).
Singapore has pioneered AI Verify, the world’s first AI testing and assurance framework, offering tools for developers and regulators to benchmark responsible AI use. Though not climate-specific, such frameworks are vital when deploying AI in sensitive sectors such as adaptation and resilience (IMDA).
Together, these policies indicate a growing recognition that AI is no longer just a technology issue, but part of the infrastructure for climate resilience.
AI for climate resilience must be matched by safeguards. Four priorities stand out:
Gender-responsive design: AI services must be accessible in local languages, low-bandwidth formats, and actively address women’s digital exclusion.
Data rights: Climate AI relies heavily on household, land, and community data; governance must align with India’s Data Protection Act and ASEAN frameworks.
Community governance: Indigenous and grassroots groups must have a voice in data sovereignty, as seen in Mekong initiatives.
Evidence and transparency: Claims about gendered climate impacts (such as “80% of the displaced are women”) require careful validation to ensure accountability and avoid narrative distortions.
At Oneworld Colab (OwC), we see AI as part of the core infrastructure for inclusive climate action. For South and Southeast Asia, the central question is not whether AI will be used in climate response, but whose needs it will serve. OwC is building a knowledge hub on AI for climate—tracking innovations, spotlighting implementors, analysing policy, and mapping funding flows. We believe AI can serve as a bridge: between communities and capital, between indigenous knowledge and data systems, and between global philanthropy and local resilience. If you are developing or funding AI-for-climate initiatives with a strong gender or community lens, we invite you to share. Together, we can make sure AI is not only efficient, but also equitable, inclusive, and transformative.
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