Policy Learning for AI Legislation: A Comparative Analysis of the EU Act and Implications for Iran

Document Type : Original Article

Authors

1 Assistant Professor ,Public Policy Department, Faculty of Management, Imam Sadiq University (AS), Tehran, Iran.

2 Ph.D. Candidate in Public Administration (Public Policy), Faculty of Islamic Studies and Management, Imam Sadiq University (AS), Tehran, Iran.

Abstract

In today's fast-paced world, Artificial Intelligence has become a primary governance issue, intensifying the need for suitable policymaking. This descriptive-analytical study, utilizing library resources, seeks to answer the: "What lessons can the policy learning mechanism derive from the European Union's AI Act for shaping the legal framework of Artificial Intelligence in the Iran?" The research methodology is based on the policy learning mechanism, operationalized through a comparative study of the EU AI Act and the situation in Iran across five operational steps. The findings reveal seven key lessons for policymaking in Iran, which include risk-based classification, transparent accountability, prohibition of prohibited uses, formulation of technical/ethical requirements, enhanced accountability, innovation-driven regulation, and establishment of independent/efficient regulatory/executive bodies. Consequently, some of these principles are either absent or require operationalization in Iran, while others are partially present. Leveraging these principles and adapting them to indigenous contexts can facilitate the formulation of an effective, comprehensive, and responsible legal framework for AI in the Iran.

Keywords

Comparative Studies in Public Administration
Volume 3, Issue 4
February 2026
Pages 203-225

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History

  • Receive Date: 31 August 2025
  • Revise Date: 24 December 2025
  • Accept Date: 14 February 2026

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