Allocating Responsibility in Autonomous AI Systems: A Tiered Governance Model Under EU Regulation

Autonomous artificial intelligence (AI) systems increasingly participate in decision-making processes that affect individuals, markets, and public administration. Their growing autonomy complicates the attribution of legal responsibility, particularly within regulatory frameworks that were designed around identifiable human actors and relatively stable products. Although European Union instruments such as the GDPR, the AI Act, and the revised Product Liability Directive address specific dimensions of risk and compliance, they do not fully resolve how responsibility should be allocated across the lifecycle of complex AI systems. The difficulty does not lie so much in the absence of legal rules. Rather, it reflects the structural tension between traditional liability models and the distributed architecture of contemporary AI development and deployment. By examining how existing EU regulatory instruments interact, the paper identifies fragmentation in responsibility allocation that may weaken institutional accountability. It then proposes a tiered model of legal responsibility based on meaningful control at different stages of system design, deployment, and operational oversight. Rather than introducing new forms of legal personhood, the model seeks to clarify how existing doctrines can be interpreted and coordinated in order to maintain regulatory coherence and socially intelligible accountability in digitally mediated environments. The model allocates responsibility according to meaningful control within distributed systems, offering a structurally coherent alternative for EU governance.