AIFl@sh is a monthly collection of critical upgrades and changes across the GCC’s AI landscape – with a smattering of relevant changes from outside of the region. Released as a newsletter on LinkedIn, we will also feature AIFl@sh on our website.

GCC

Kingdom of Saudi Arabia

Year of AI

In March, the Saudi Cabinet declared 2026 to be the “Year of Artificial Intelligence,” led by the Saudi Data & AI Authority (SDAIA). Reflecting the government’s desire to harness AI to drive economic diversification, build societal benefits and establish international leadership in the digital era, this national initiative elevates AI as a strategic priority under Vision 2030, aiming to accelerate innovation, strengthen governance and position the kingdom as a global hub for advanced technologies by focusing on expanding AI ecosystems, building workforce competencies, attracting investment and reinforcing ethical and responsible AI use.

Kingdom of Bahrain

No new Bahrain-specific AI law or policy update was identified for March 2026.

The United Arab Emirates

International stance on AI policy

The UAE’s international stance on AI policy (released in September 2024) outlines the country’s vision for engaging with global AI governance and contributing to the development of international standards. The policy emphasises the UAE’s commitment to responsible AI use, ethical principles and collaboration with multilateral organisations to shape the future of AI regulation worldwide. It positions the UAE not only as a regional leader in AI adoption but also as an active participant in global discussions on AI ethics, safety and innovation, reinforcing its ambition to be a trusted voice in international AI diplomacy.

Sultanate of Oman

No new Oman-specific AI law or policy update was identified for March 2026.

State of Qatar

No new Qatar-specific AI law or policy update was identified for March 2026.

State of Kuwait

No new Kuwait-specific AI law or policy update was identified for March 2026.

International

Singapore

Model AI governance framework for agentic AI

Singapore’s Infocom Media Development Authority (IMDA) released a Model AI governance framework for agentic AI in January 2026, setting guardrails for organisations deploying advanced AI agents, focusing on governance, human oversight, risk management and transparency. The framework aims to help companies implement AI systems responsibly while maintaining accountability and trust.

South Korea

AI Basic Act

The Government of South Korea enacted the AI Basic Act in January 2025, with implementation from January 2026. The act establishes a national legal framework for AI, supporting innovation while ensuring safety and reliability. It introduces requirements for high-impact AI systems, transparency obligations and national AI governance structures.

Australia

Policy for the responsible use of AI in government

The Australian Digital Transformation Agency released a policy to guide the responsible use of AI across government agencies, requiring agencies to implement governance controls, assign accountability for AI systems and maintain transparency about how AI is used in public services.

United States of America

Department of Energy – Generative AI policy

The U.S. Department of Energy (DOE) issued a policy to regulate the internal use of generative AI tools within the department, focused on data protection, cybersecurity and risk management.

Department of Homeland Security – Roles and responsibilities framework for AI in critical infrastructure

The U.S. Department of Homeland Security (DHS) published a framework to define roles and responsibilities of stakeholders involved in AI systems used in critical infrastructure. It aims to strengthen accountability, improve risk management, and ensure the safe deployment of AI across essential sectors.

Government Accountability Office – AI accountability framework

The U.S. Government Accountability Office (GAO) released an AI accountability framework to guide federal agencies in the responsible use of AI. The framework outlines governance, risk management, performance monitoring and transparency practices to ensure AI systems are trustworthy and accountable.