Climate change represents one of the most urgent global crises, characterised by rising temperatures, extreme weather events, and ecosystem degradation. This paper explores the application of artificial intelligence (AI) to mitigate and adapt to climate change, focusing on agricultural greenhouses as a representative problem domain. The study presents a Business Process Model and Notation (BPMN) framework that integrates Internet of Things (IoT) devices, satellite data, and AI algorithms for real-time climate monitoring, data analysis, decision support, and policy engagement. Ethical considerations—fairness, accountability, transparency, and environmental sustainability—are critically examined to ensure the responsible deployment of AI. The paper reviews current AI applications across energy systems, precision agriculture, carbon capture, urban planning, and climate policy, highlighting benefits such as reduced energy waste, optimised resource allocation, and evidence-based policymaking. Challenges, including high energy consumption of AI models, data scarcity, and equity concerns, are discussed. The analysis reveals research gaps where fewer AI methods are applied, particularly in energy trends and public perception studies. Ultimately, responsible AI implementation—guided by ethical principles and inclusive access—offers transformative potential to advance climate action while minimising its own environmental footprint.