Enhancing nuclear technology into battling with seawater pollution is one of the most complex challenges; however, it gives a particularly robust aspect to artificial intelligence for achieving SDG 14 (Life Below Water). For example, this kind of tracking radioisotope makes it possible for scientists to determine, trace and quantify contamination, sourcing pollution, and monitoring global changes in the oceans very accurately. These processes are very important in depositing heavy metals, cleaning up oil spills and potentially radioactive activity in marine systems. In addition to nuclear approaches, there is an AI approach in working with massive datasets derived from satellite images, and remote sensing technology, which can model pollution patterns and identify significant hotspots. Machine learning sports tools that would classify patterns in pollution using historic and up-to-date information and encourage the prediction of strategic models on interventions regarding pollution for a better treatment of prevention and the distribution of resources for optimum efficacy. This is achieved through the use of AI-managed robots and drones in water to survey and clean up the pollution as well as to carry out environmental assessments by removing physical garbage.