Mind The Gap: How The Technical Mechanism Of Agentic AI Outpace Global Legal Frameworks

TL;DR

This paper systematically compares definitions of agentic AI across global regulations and developer architectures, revealing a persistent gap between legal and technical understandings that hampers effective regulation.

Contribution

It identifies and analyzes the definitional inaccuracies in current regulatory frameworks and proposes a technical consensus definition of agentic AI.

Findings

Legal definitions conflate model capability with agentic architecture.

Regulatory instruments are structurally incapable of governing actual AI mechanisms.

A technical consensus definition of agentic AI is proposed.

Abstract

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.