Artificial intelligence and the re-specification of engineering competence in water systems: a digitally mediated infrastructure perspective

Artificial intelligence is increasingly used in water systems for monitoring, prediction, optimisation and decision support. However, current scholarship remains strongly focused on technical performance, with less attention to how artificial intelligence reshapes engineering competence, professional judgement and infrastructure governance. This article develops the Digital Water Engineering Competency Framework (DWECF) to define the competencies required for engineers working in digitally mediated water infrastructure systems. A structured narrative synthesis was used to examine literature on artificial intelligence in water systems, engineering education, socio-technical infrastructure governance and responsible digital decision-making. The synthesis identified six interdependent competence domains: data and measurement literacy; AI-assisted infrastructure operations; digital water safety and risk management; institutional and regulatory competence for AI systems; cyber-physical infrastructure awareness; and ethics and public accountability. The main contribution is a competency framework that links technical AI capability with institutional capacity, risk governance and public legitimacy. The analysis shows that AI-enabled water systems require engineers who can interpret uncertain data, evaluate model outputs, recognise cyber-physical risks and maintain accountability in automated or semi-automated decision environments. The framework is particularly relevant to water systems operating under data scarcity, infrastructure fragility and institutional constraint, where digital tools may improve visibility without necessarily improving outcomes. The article contributes to Environmental Challenges by positioning digital water transformation as both a technical and governance challenge requiring new forms of professional competence.