The growing threat of groundwater pollution, exacerbated by industrial activities, agricultural runoff, and urban development, necessitates innovative management strategies. Conventional approaches to monitoring and mitigating groundwater contamination often fall short due to their reactive nature and high resource demands. This chapter delves into the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) for proactive groundwater pollution control and management. It begins with discussing the primary sources of groundwater pollution and the foundational concepts of AI and ML. The chapter then explores creating and deploying of predictive models designed to identify pollution hotspots and anticipate contaminant movement. It also looks at how machine learning techniques and real-time data integration might improve groundwater management choices. An examination of the difficulties and moral dilemmas surrounding the application of AI and ML in environmental stewardship rounds off the chapter. This chapter highlights the potential of AI and ML to transform groundwater management through case studies and current technology developments, offering scalable solutions that contribute to the preservation of water resources for future generations.