Artificial intelligence (AI), a rapidly advancing technological field, is significantly revolutionizing the ways in which environmental crime detection and prevention are being approached by substantially improving the efficiency and effectiveness of monitoring systems while also enabling advanced predictive analysis capabilities. This paper meticulously examines and reviews three pivotal studies that delve into the diverse applications of AI within the realms of environmental governance, pollution prevention, and the detection of criminal activities related to environmental degradation and harm. The findings from these studies illuminate and underscore the remarkable potential of AI to not only enhance enforcement measures designed to uphold environmental laws but also to accurately identify the sources of pollution while simultaneously predicting potential violations before they occur. However, it is important to acknowledge that several challenges persist, including issues related to data bias, the necessity of ethical considerations, and the complexities inherent in governance structures that must be navigated in order to successfully implement AI technologies. Future advancements in this field must concentrate on the critical tasks of refining AI models to improve their accuracy and reliability, ensuring a high level of transparency in their operations, and promoting a framework for equitable environmental management that benefits all stakeholders involved in the process.