When weighed carefully, the trade-offs between AI’s benefits and its constraints tend toward positive outcomes when guided by strong policy and sustainability commitments.
As Indonesia faces intensifying climate impacts from rising temperatures and shifting rainfall patterns to more frequent extreme weather, new tools are emerging to help understand, adapt to, and mitigate these challenges. One of the emerging tools is artificial intelligence (AI): a field rapidly being developed and adopted across Indonesia in both the public and private sectors to address complex data challenges, forecast future risks, and strengthen climate resilience.
AI Development and Adoption in Indonesia
Indonesia’s digital ecosystem is expanding quickly, and AI is increasingly integrated into national development strategies. The government is finalizing its first national AI roadmap, aimed at guiding infrastructure and sector-specific AI adoption across healthcare, agriculture, climate, and digital services, while attracting foreign investment and building local capabilities.
One of the most tangible benefits of AI in Indonesia’s climate response is in data integration, analysis, and prediction. Accurate climate tracking depends on real-time data from multiple sources, including weather stations, air quality sensors, satellite imagery, health surveillance, and economic activity. AI excels at making sense of this complex, high-volume data.
For example, Indonesia has launched advanced data systems to boost emissions monitoring and transparency, including improvements to its climate registry to support more accurate tracking of greenhouse gases across sectors.
In public health, Indonesia unveiled ClimateSmart Indonesia, an AI-powered platform designed to predict and respond to climate-sensitive diseases such as malaria and dengue. By integrating climate, health, and mobility data, this platform uses predictive models to support decision-makers with early warnings and adaptive responses, a critical step in protecting vulnerable populations as climate shifts intensify disease risks.
AI is also being used in agriculture, natural resource management, and disaster risk reduction, from predicting crop stress under drought conditions to modeling landslide and flood risks. By forecasting hazards earlier and with greater precision, communities and governments can prepare and respond more effectively.
Energy Use and Climate Trade-offs
However, AI’s benefits come at the cost of significant energy demands. Large-scale AI systems, those used for machine learning, deep learning, and massive data processing, require considerable computing power. This, in turn, means more electricity consumption and potential increases in associated carbon emissions if powered by fossil fuels.
Managing the tension between AI’s promise and its energy requirements is critical for Indonesia as it pursues both digital transformation and climate goals.
When weighed carefully, the trade-offs between AI’s benefits and its constraints lean toward positive outcomes, if guided by strong policy and sustainability commitments. In Indonesia, AI can amplify climate action in ways previously unimaginable: improving emissions-tracking accuracy, strengthening early-warning systems, optimizing renewable-energy grids with predictive models, and enhancing public-health resilience.
To realize these benefits equitably, Indonesia must invest in energy transitions that rapidly expand renewable electricity, improve grid flexibility, and ensure AI infrastructure runs on low-carbon power. The Just Energy Transition Partnership and national efforts to decarbonize the grid will be important in this context, as will policies that incentivize clean energy use for data centers and digital infrastructure.
Looking ahead, AI can be a catalyst for Indonesia’s Paris Agreement commitments by enabling more precise emissions measurement, faster adaptation responses, and smarter planning across sectors.
This post is submitted by Climate Scorecard Country Manager, Netra Naik.