This review aims to discuss how Artificial Intelligence (AI) can play a critical role in engineering innovations for climate change solutions. The review analyzes AI's employment in domains such as renewable energy systems, sustainable construction, and environmental engineering as it reveals its adaptability to tackle the impact of climate change. AI integration with IoT and machine learning optimizes the use of energy and resources and improves urban planning. Because of the role AI plays in renewable energy-related aspects such as predictive maintenance, energy optimization, and grid management, energy can be efficiently delivered from renewable sources. In construction, AI-driven tools like Building Information Modeling (BIM) and digital twins promote sustainable practices by reducing waste and improving energy efficiency. In environmental engineering, AI and Internet of Things (IoT) simplify data analysis to get real-time data for smart city planning and resource utilization. Still, the review also reveals limitations to the deployment of AI, such as data dependencies, algorithmic bias, and socioeconomic inequities, especially in underdeveloped regions. There are other challenges, such as ethical issues and the need for specialized knowledge. Finally, the study emphasizes the importance of interdisciplinary collaboration, supportive policies, and investment in AI research focused on fairness and environmental sustainability to overcome these challenges. It concludes that while AI offers significant potential for addressing climate change, realizing its full benefits requires addressing ethical, financial, and technological barriers through inclusive policies and global cooperation.
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Inam et al. (Mon,) studied this question.
www.synapsesocial.com/papers/698c1bdc267fb587c655dd47 — DOI: https://doi.org/10.31841/kjet.2025.44
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