From Big Data to Big Justice: AI and Automation in EU Consumer Collective Redress

Abstract Mass harm events occur increasingly in the single market, with representative actions set to serve as a tool to address rational apathy of consumers in pursuing their claims. This article asks (i) how far artificial intelligence and automation tools can enhance the efficiency and effectiveness of EU consumer collective redress mechanisms and (ii) under what conditions such tools remain compatible with fundamental rights protections and the EU’s emerging AI acquis . Drawing on doctrinal comparison of Representative Actions Directive (RAD) transposition/implementation in the national laws of five Member States (the Netherlands, Czechia, Slovakia, France, and Germany) and on a mapping of AI use cases across the redress lifecycle, it is argued that algorithmic enrolment, evidence mining, and redress distribution can reduce (pre-)litigation costs significantly and simplify the relevant processes, thereby further helping combat the consumer “rational apathy.” Yet, the same technologies are classified as high risk under the AI Act, which could expose the courts, lawyers, and qualified entities to novel accountability considerations. Therefore, appropriate safeguards will have to be taken to reconcile “big data” in enforcement with “big justice.”