The global crisis of climate change has intensified the competition for access to subterranean resources. For example, approximately 70% of groundwater utilised in Germany is primarily allocated for irrigation and drinking purposes. A traditional method for extracting groundwater entails the construction of a well or borehole. According to the Law of Geological Data (Geologiedatengesetz), private proprietors who drill boreholes are subject to liability and registration requirements. Across the globe, the demand for private or commercial management of boreholes is increasing. In recent decades, countries such as Syria, Iran, Iraq, Morocco, and India have reported incidents involving borehole accidents, raising the question, “Are we trapped in a cycle where solutions become the cause of subsequent problems?” This societal issue predominantly affects developing nations and has become a source of political instability. The fundamental causes of this problem include overpopulation, a lack of responsibility among governmental officials, and a deficiency of accountability among the populace. Currently, the remedial techniques employed involve either a chain-pull mechanism or the excavation of a parallel borehole. However, these approaches are regarded as insufficient due to their time-consuming nature and the safety risks involved. In the technological era, robotic systems are pioneering transformative solutions in inspection and maintenance. This paper introduces an innovative, socially responsible robotRobot that integrates robotics and computer vision, thereby expanding the scope of applied research. The robotRobot utilises well-defined data points, employs robotic vision, and classifies boreholes using deep neural networks to significantly replace human inspectors and promote robotic process automation.