This summary was prepared by Hamed Kioumarsi, a member of the Editorial Board at Springer Nature, in collaboration with Majid Mardani Sefidmezgi and Saeed Mehrjou from the Economic, Social, and Extension Research Department, Gilan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran.

Citation: Kioumarsi, H., Mardani Sefidmezgi, M., & Mehrjou, S. 2026. AI and Climate Change Communication. Springer Nature Community.  https://go.nature.com/4ttQpm1

Introduction

The world around us is shrinking each day, and connections between individuals continue to increase through travel and social media applications. AI is also changing the way we live our lives today, and it plays a critical role in the transmission of information regarding climate change issues. Indeed, climate change communication is one key component of building awareness for this issue and taking action to address its impacts on society. However, climate change communication has traditionally faced challenges in being too complex scientifically, misinformation, and the lack of access and personal relevance. New developments in AI, namely conversational AI, machine learning, and generative AI, are some possible means of breaking these down barriers to effective climate change communication.

Communication

AI climate communication tools will continue to become more and more important in helping to make sense of climate change communication. AI climate communication usually relies on using data, machine learning, and natural language processing to provide insight, forecast, and action. One hopeful trend in AI climate communication involves the launch of ChatClimate. This is a climate chatbot AI designed to tie down the information coming out of a large language model (LLM) to authoritative climate science, specifically, the IPCC's Sixth Assessment. What this AI does is make the information provided more accurate, timely, and reliable. The use of chatbots like these is a good way to supplement the work of human experts while translating climate science into conversational English.

The Role of AI in Scientific Assessment

Apart from facilitating direct interaction, artificial intelligence provides support to the scientific process involved in communicating about climate change. Scientists talk about using AI-based systems to address the ever-increasing amount of information concerning climate change to make such assessments carried out by institutions like the IPCC more efficient and rigorous. The use of machine learning techniques will assist in automating processes within evidence synthesis and thus making reports more timely and comprehensive. Such measures would contribute to climate change communication as far as making synthesized scientific information timely is concerned. In addition, the report mentions the need for the creation of governance measures regarding the use of AI in climate science to maintain scientific integrity since any AI system should complement rather than take over human expertise.

Opportunities and Challenges

The use of AI in climate change faces two challenges that are also opportunities for improvement. First, AI-powered algorithms may help to find an optimal solution for reducing emissions through assessing the industries' processes and their energy consumption, transportation data, and other information. Second, climate change adaptation may become possible due to predictive models created for predicting natural disasters. At the same time, the energy required for AI operation generates greenhouse gases, which requires the implementation of appropriate governance for having a positive effect on the environment overall. Another crucial challenge that needs addressing is misinformation. It is necessary to develop AI-powered platforms that provide accurate and relevant information to users.

Current Research and Future Directions

The results of bibliometric studies show exponential growth in scientific articles on AI and climate with main themes of decision support systems, machine learning, and communications. Current research trends suggest an interaction across different disciplines of AI, climate science, social sciences, and public communication. Personalized and localized communication supported by AI technology is a promising avenue of future research that needs more exploration to achieve a balance between precision, accessibility, and scalability. Future climate communication systems based on AI technology would utilize real-time data, sophisticated visualizations, and advanced interfaces to give climate science practical applications.

References

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