Next-Generation Environmental Management: A Review of Artificial Intelligence for Ecosystem Monitoring and Sustainable Decision-Making

Abstract

Artificial Intelligence (AI) has become one of the disruptive technologies in environmental management, providing new ways of monitoring the ecosystem, optimising resources, and making environmentally friendly decisions. This review examines how AI can potentially be used in different environmental areas, such as biodiversity monitoring, ecological change predictions, and how natural resources can be better distributed. Thanks to the incorporation of AI technologies like machine learning, remote sensing, and Internet of Things sensors, real-time data acquisition and analysis can now be conducted, which allows for more informed and timely decisions related to the environment. Predictive models based on AI offer useful information on the possible effects of climate change, loss of biodiversity, and habitat degradation to enable policymakers to engage in proactive environmental management. Nonetheless, the use of AI in environmental governance does not come without its problems. Challenges like data quality and availability, the complexity of ecosystems, ethics, and technological constraints need to be resolved to guarantee the effectiveness and equity of AI-based solutions. This paper addresses these issues and outlines future research opportunities, focusing on the importance of interdisciplinary cooperation and building a strong data infrastructure to maximize the potential of AI. With these obstacles resolved, AI has the potential to become a key factor in sustainability and resilience in ecosystems around the world.