The aim of the work is to systematize the philosophical and methodological problems of the introduction of AI in hydraulic engineering and to propose a conceptual framework for its responsible implementation, ensuring not only technological efficiency, but also social legitimacy, engineering safety and environmental sustainability. The implementation of artificial intelligence (AI) technologies in the field of hydraulic engineering opens up new opportunities for improving the efficiency of water resources management, monitoring the condition of hydraulic structures (HS), and forecasting hazardous processes. However, this process is accompanied by a complex of methodological, regulatory, and ethical problems. The aim of the research is to systematize the key philosophical and methodological challenges related to the epistemological limitations of AI models, the ontological status of digital twins, the redistribution of responsibility, issues of cyber resilience, and socio-ecological justice. The methodology is based on an interdisciplinary literature analysis and case studies of typical tasks (flood management, cavitation diagnostics, filtration monitoring). As a result, the necessity of integrating AI not as a replacement for engineering judgment, but as a tool embedded in a system of professional procedures and public control is substantiated. As a conceptual framework, the principles of technological humility are proposed, including transparent model audit, lifecycle management, and clear role distribution. It is concluded that successful implementation requires a paradigm shift from searching for the “most accurate algorithm” to building robust socio-technical systems that ensure not only technological efficiency but also social legitimacy, engineering safety, and environmental sustainability.