Mind The Gap: How The Technical Mechanism Of Agentic AI Outpace Global Legal Frameworks
For policymakers and AI developers, this work highlights a critical mismatch that undermines effective governance of agentic AI systems.
This paper reveals a persistent definitional gap between legal and technical definitions of agentic AI, showing that current regulatory instruments (e.g., EU AI Act, OECD/G7 Principles) fail to capture the actual mechanisms of agentic systems. The authors propose a consensus technical definition and demonstrate that definitional imprecision renders regulations structurally incapable of governing agentic autonomy.
This article presents the first systematic comparative survey of how public bodies, international organisations, national regulators, and the private sector define agentic artificial intelligence, identifying the technical inaccuracies pervading each definition. Analysing eleven regulatory instruments and industry frameworks -- including the EU AI Act, the OECD/G7 Principles, NIST, the UK ICO, and the European Commission -- alongside six leading developer architectures, this study demonstrates a persistent definitional gap: legal definitions consistently conflate model capability with agentic architecture, attribute cognitive deliberation to probabilistic token prediction, and treat autonomy as a scalar property rather than a structural shift from single-inference to iterative execution loops with tool integration. A consensus technical definition synthesised from developer documentation is proposed. The article examines the consequences of this gap, demonstrating that definitional imprecision produces regulatory instruments structurally incapable of governing the actual mechanisms -- system prompts, API permissions, sandboxing, and orchestration code -- that constitute agentic autonomy.