Artificial Intelligence in Environmental Communication: Transforming Climate Change Awareness, Public Engagement, and Sustainable Decision-making
Jonathan Kuffour Owusu *
Department of Geosciences, Fort Hays State University, Hays, Kansas USA.
Edna Beverla
Information Services Department, Okere District Assembly, Ghana.
Tope Joseph Arayombo
Department of Agricultural, Leadership, Education and Communication, Univeristy of Georgia, Athens, USA.
Oluwafunmilayo Esther Ajiferuke
Department of Agricultural, Leadership, Education and Communication, Univeristy of Georgia, Athens, USA.
Emmanuel Toochukwu Ogbodo
Department of Media, School of Culture and Communication, Swansea University, Swansea, Wales, UK.
*Author to whom correspondence should be addressed.
Abstract
Environmental communication has become central to how societies interpret climate change and decide how to respond, and artificial intelligence (AI) is reshaping the practices through which climate information is produced, circulated, interpreted and acted upon. This critical narrative review examines the intersection of AI and environmental communication across three connected domains: public awareness of climate change, public engagement, and sustainable decision-making. Evidence was drawn from peer-reviewed scholarship in communication studies, environmental social science, computational linguistics and sustainability research, selected for relevance, methodological adequacy and contribution to the review question rather than for citation frequency alone. The synthesis distinguishes three functional roles that AI performs in this field: a generator of accessible and personalised content, an analytic instrument for sensing public discourse at scale, and an intermediary that curates the information people encounter. The available evidence indicates that AI can widen access to climate science, tailor messages to previously unengaged audiences, and reveal patterns in public sentiment that conventional survey methods struggle to capture. These benefits are qualified by recurring problems of factual accuracy, opacity, and uneven representation across languages and regions, and the same generative capacity that supports outreach can be turned to greenwashing and the manufacture of persuasive misinformation. For decision-making, AI shows conditional rather than uniform value, narrowing the gap between environmental intention and action in some contexts while risking a decoupling of communicative signals from substantive change in others. Confidence in many conclusions is constrained by short observation windows, concentration on a small number of platforms and high-income settings, and a scarcity of longitudinal behavioural evidence. The review identifies priorities for research, including standards for accuracy and provenance, equity-centred design, and durable behavioural evaluation, and argues for treating AI as an object of critical scrutiny within environmental communication rather than an unqualified solution.
Keywords: Artificial intelligence, climate change communication, public engagement, misinformation, large language models, sustainable decision-making, science communication, environmental communication.