AIReL · AIReL: AI Regulatory Learning for Compliance with the EU AI Act

The EU AI Act is the world’s first major legislative framework for high-risk AI systems. Its ambition to regulate both technological and societal risk creates challenges for national regulators tasked with interpreting and enforcing its provisions. The AIReL (AI Regulatory Learning) project addresses a critical implementation gap: how to identify which compliance requirements are difficult to formalise, and how to support regulatory learning where interpretive uncertainty is high.Bridging law, political science, legal informatics, and strategic foresight, the project introduces a replicable method for diagnosing the ‘semantic fragility’ of legal provisions; that is, their resistance to being operationalised into structured or automatable compliance tools. It hypothesises that provisions with higher semantic fragility require more adaptive regulatory learning mechanisms to ensure compliance.To test this, AIReL builds scenarios of embodied AI deployment in healthcare and eldercare by 2035, which are sectors where overlapping regulation and vulnerability of end-users raise the stakes of failure. Through participatory simulation exercises with Irish regulators and oversight bodies, the project observes how learning tools are selected under different fragility conditions. The results are synthesised into a regulatory learning tool catalogue and briefings with guidance for national and EU oversight actors. All outputs will be openly accessible and formatted for uptake in real-world policy environments.The project is hosted at Trinity College Dublin’s ADAPT Centre and supervised by Prof. Dave Lewis, a recognised expert in trustworthy AI and data governance. The researcher combines academic expertise in EU policy and law with nearly a decade of professional experience in EU affairs and strategic foresight at the European Space Agency.