Regulatory Treatment of AI Agents Acting on Behalf of Consumers

Abstract

Background: Questions surrounding AI agents are administrative as well as legal because institutional practice can influence consumer law, consistency, and accountability.

Objective: Our objective was to determine how institutional arrangements concerning AI agents influenced implementation consistency and outcomes related to consumer law.

Methods: The study compared 5 jurisdictions or institutional settings using legal and policy documents, structured organizational evidence, and where relevant key-informant material. A common framework examined authority, coordination, transparency, procedural safeguards, enforcement, and implementation capacity.

Results: Comparative coding revealed three dominant patterns of AI agents implementation. Explicit mandates, coordination arrangements, and accessible review mechanisms characterized the higher-performing cases and were associated with a 16% increase in the composite score. Fragmented responsibility was associated with both delay and inconsistent enforcement.

Conclusion: Implementation conditions appear decisive for the effectiveness of policy relating to AI agents. Accordingly, public-sector AI rules are unlikely to be effective without operational capacity, transparent oversight, and clearly assigned responsibility.

Study design: comparative regulatory study.

Publication history: Originally published in print on 15 June 2026, Volume 6, Article 4. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.