article · Next Sustainability
Artificial intelligence offers significant potential to support the transition to net-zero emissions and combat climate change. Evidence shows AI can optimise energy systems, refine climate modelling and forecasting, enhance emissions tracking, and boost sustainability across sectors such as agriculture, transport, and waste management. However, several barriers complicate deployment. These include issues with data availability, quality, and privacy, alongside concerns regarding algorithmic bias, fairness, governance, human collaboration, and the substantial energy consumption of AI systems themselves. Successfully scaling these technologies requires coordinated efforts in policy development, targeted investment, capacity building, and collaborative partnerships. While AI provides powerful mechanisms for climate change mitigation and adaptation, realising these benefits depends on addressing systemic operational and ethical hurdles.
Reaching net-zero targets requires rapid decarbonisation across entire economies. Understanding how artificial intelligence can accelerate sustainability, while recognising its practical limitations and energy demands, helps decision-makers direct resources effectively. It provides a balanced view for organisations seeking technological solutions to climate change without overlooking critical risks.
Potential applications span automated energy management, precision agriculture, route optimisation in transport, and corporate emissions tracking software. Prospective users include grid operators, logistics firms, agricultural enterprises, and environmental compliance teams. Because the review synthesises broad trends rather than testing a specific tool, individual applications range from early-stage conceptual models to commercially available tools facing scaling and regulatory challenges.
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This comprehensive review explores the nexus between AI and the pursuit of net-zero emissions, highlighting the potential of AI in driving sustainable development and combating climate change. The paper examines various threads within this field, including AI applications for net zero, AI-driven solutions and innovations, challenges and ethical considerations, opportunities for collaboration and partnerships, capacity building and education, policy and regulatory support, investment and funding, as well as scalability and replicability of AI solutions. Key findings emphasize the enabling role of AI in optimizing energy systems, enhancing climate modelling and prediction, improving sustainability in various sectors such as transportation, agriculture, and waste management, and enabling effective emissions monitoring and tracking. The review also highlights challenges related to data availability, quality, privacy, energy consumption, bias, fairness, human-AI collaboration, and governance. Opportunities for collaboration, capacity building, policy support, investment, and scalability are identified as key drivers for future research and implementation. Ultimately, this review underscores the transformative potential of AI in achieving a sustainable, net-zero future and provides insights for policymakers, researchers, and practitioners engaged in climate change mitigation and adaptation.
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DOI: 10.1016/j.nxsust.2024.100041
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