---
title: "Regulating Autonomous and Agentic AI: Challenges and Solutions"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2607.21345v1"
permalink: "https://feed.astralor.com/items/itm_14885fd72ff66f1402ef9116"
published: "2026-07-23T14:13:34.000Z"
score: 81
channel: "ai"
tags: ["AI Governance","Data Protection","EU AI Act","Autonomous AI","FCA"]
---

# Regulating Autonomous and Agentic AI: Challenges and Solutions

## AI commentary

> This paper is a must-read for anyone interested in AI governance, as it is the first to clearly explain how 'autonomy' as a technical feature dismantles traditional regulatory logic. For legislators drafting AI laws and legal teams in tech companies building compliance systems, it offers a complete roadmap from 'ex-post fines' to 'ex-ante prevention.'

## At a glance

This paper examines the regulatory challenges posed by autonomous and agentic AI, where traditional assumptions about regulatee knowledge and control break down due to distributed responsibility across the AI supply chain. It studies four regulatory systems: UK content platform regulation, data protection, UK financial services, and the EU AI Act. The paper identifies systemic risks and the ineffectiveness of retrospective oversight, proposing a shift from reactive to proactive regulation to adapt to AI autonomy.

## Key points

- Autonomous AI undermines regulatory assumptions: regulators no longer have full knowledge or control, with responsibility diffused across the AI supply chain.
- Analyzes common challenges across four regimes: UK content platforms, data protection, UK financial services, and the EU AI Act.
- Retrospective oversight fails as a risk management tool, necessitating proactive, forward-looking regulatory frameworks.
- Proposes bringing the entire AI supply chain into regulatory scope and addressing new systemic risks from AI autonomy.

## Full text

Regulating activities where regulatees use autonomous and agentic AI is challenging. Regulatory assumptions about regulatee knowledge and control no longer hold true; much of that lies elsewhere in the AI supply chain which thus needs to be brought within the scope of regulation. Governance systems for autonomous AI cannot replicate existing governance models, but need a fresh approach. Retrospective supervisory oversight becomes ineffective as a risk management tool, and AI autonomy generates new systemic risks which require new solutions. This paper investigate four regulatory systems: UK regulation of content platforms, data protection, UK financial services, and the EU AI Act\'92s cross-sectoral regime. It analyses the challenges posed by autonomous and agentic AI and proposes potential solutions which regulators might adopt. These will transform regulation from a reactive process to an active one, and assist it in adapting to the challenges of AI autonomy.

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Verify against the original before citing; curated by Astral Feed: https://feed.astralor.com/items/itm_14885fd72ff66f1402ef9116