Environmental DNA (eDNA) provides a non-invasive, cost-effective approach to monitoring marine biodiversity by amplifying specific genetic markers or barcodes to identify multiple species within a water body. This paper explores the issues and challenges faced by eDNA technology in the marine sector and propose how AI integration can help in addressing the problem. By leveraging machine learning algorithms, we can improve species identification accuracy, discover migration patterns, detect invasive species and anomalies when new samples deviate from predicted data. This AI-enhanced methodology ensures more reliable insights, advancing our understanding of marine ecosystems and thus taking actions to protecting species.