Using AI to advance sustainability solutions through improved data, modeling and resource management while addressing the environmental and social impacts of AI, including impacts on energy and water resources, ecosystem health and local economies.
AI and Sustainability
Ohio State advances integrated research at the intersection of artificial intelligence and sustainability, exploring how AI can enhance discovery, decision-making and implementation across complex environmental and societal systems while examining the sustainability implications of rapidly expanding digital infrastructure. The university fosters and supports collaborations among data scientists, engineers, social scientists, planners and community partners to develop AI-enabled approaches that strengthen resilience, improve resource management and support climate and sustainability transitions. As a cross-cutting area, AI and Sustainability enhances all Sustainability Institute research priority areas, strengthening analytic capacity, accelerating discovery and supporting coordinated action across complex sustainability challenges.
This work also includes the sustainability of AI itself. Researchers develop predictive models, digital twins, decision-support platforms and participatory analytics that improve sustainability planning and operations, while also examining the energy, water, materials and governance dimensions of AI systems. Together, these efforts support responsible AI innovation that advances sustainability goals while minimizing unintended environmental and social consequences.
AI-Enabled Sustainability Discovery and Decision Support
Researchers apply machine learning, remote sensing and advanced analytics to improve climate forecasting, ecosystem monitoring, circular economy strategies and sustainable infrastructure planning, enabling more timely and informed sustainability decision-making across sectors.
Sustainable and Responsible AI Systems
Ohio State researchers examine the environmental footprint of AI infrastructure, including energy and water use, data center design and lifecycle impacts, while developing approaches for efficient computing, transparent modeling and responsible AI governance aligned with sustainability goals.
AI for Community Resilience and Participatory Sustainability
Using integrated environmental and socio-economic data, researchers develop AI-supported tools that help communities assess risk, co-design interventions and strengthen preparedness strategies while ensuring accessibility, equity and local relevance in AI-enabled sustainability solutions.
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