AI Applications in Environmental Conservation and Biodiversity Management

Artificial Intelligence has emerged as a transformative force in addressing global environmental challenges and biodiversity loss. Rapid advances in machine learning, computer vision and data analytics have enabled more efficient monitoring prediction and management of natural ecosystems. This paper explores the role of AI applications in environmental conservation and biodiversity management with particular emphasis on information technology driven solutions. The study reviews existing literature to examine how AI tools such as remote sensing predictive modeling and intelligent decision support systems contribute to wildlife protection, habitat conservation, climate change mitigation and sustainable resource management. A qualitative methodology based on secondary data from peer reviewed journals reports and institutional publications is adopted. The analysis highlights how AI enhances accuracy, scalability and responsiveness in conservation efforts while also raising ethical governance and data related concerns. The findings indicate that AI does not replace human ecological expertise but complements it by enabling data driven insights and timely interventions. The paper concludes that responsible and transparent deployment of AI technologies is essential to ensure long term ecological sustainability and biodiversity preservation.