Artificial Intelligence Regulation in Pakistan: Lessons from Australia's Risk-Based Approach and Germany's EU AI Act Compliance for Developing a Contextually Adaptive Legal Architecture

Authors

  • Barrister Dr. Anwar Baig Professor of Law & Practice, Senior Legal Practitioner, Islamabad – Pakistan

DOI:

https://doi.org/10.63954/WAJSS.5.1.43.2026%20

Keywords:

Artificial Intelligence Regulation, Pakistan National AI Policy 2025, EU AI Act, Australia AI Governance

Abstract

The rapid proliferation of artificial intelligence (AI) technologies presents both unprecedented opportunities and significant regulatory challenges for developing nations. Pakistan, having recently adopted its National AI Policy 2025, stands at a critical juncture in formulating a legal architecture that balances innovation with citizen protection. This article examines two contrasting yet complementary regulatory paradigms: Australia's evolving risk-based approach to AI governance and Germany's implementation of the European Union's AI Act. Through comparative analysis, it explores how Pakistan can develop a contextually adaptive legal framework that acknowledges its unique socio-economic realities, technological infrastructure, and institutional capacities. The article argues that Pakistan should adopt a phased, risk-based regulatory model that leverages existing data protection frameworks, establishes dedicated oversight mechanisms, and prioritises human-centred AI governance while avoiding the regulatory rigidity that may stifle innovation. Drawing from Australia's voluntary-to-mandatory transition and Germany's institutional adaptation to EU requirements, this analysis offers actionable recommendations for Pakistan's emerging AI regulatory architecture.

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Published

2026-03-30

How to Cite

Barrister Dr. Anwar Baig. (2026). Artificial Intelligence Regulation in Pakistan: Lessons from Australia’s Risk-Based Approach and Germany’s EU AI Act Compliance for Developing a Contextually Adaptive Legal Architecture. Wah Academia Journal of Social Sciences, 5(1), 826–838. https://doi.org/10.63954/WAJSS.5.1.43.2026