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Egypt AI Governance
Egypt's AI governance framework pairs the National AI Strategy 2025-2030 with the March 2026 National Guidelines for Trustworthy and Responsible AI, establishing risk-proportionate governance obligations for government, enterprise and community actors across the AI lifecycle.
Egypt ranks first in Africa in the Oxford Insights Government AI Readiness Index and has adopted a two-part governance approach: the second edition of its National AI Strategy (2025-2030) and the National Guidelines for Trustworthy and Responsible AI, published in March 2026 by the Egyptian Center for Responsible AI (ECRAI) under the supervision of the National Council for Artificial Intelligence, Quantum Computing and Emerging Technologies (NCAI). The strategy rests on six pillars (governance, technology, data, ICT and AI infrastructure, ecosystem, talent) with 21 initiatives, including Arabic large language models, and targets a 7.7 percent ICT contribution to GDP, 30,000 trained AI experts and more than 250 AI companies by 2030.
The guidelines apply to all actors in the AI ecosystem, classified as government, enterprise or community, acting as provider-developer or beneficiary-user. They are structured around four pillars: institutional governance (mandatory Chief AI Officer or AI governance committee, risk-tiered AI system inventory from Tier 1 to Tier 4, workforce training), AI lifecycle governance (design documentation, bias and data-quality evaluation, TEVV pre-deployment testing, post-deployment monitoring and audits, with HITL, HOTL or HOOTL human-oversight models chosen by risk level), stakeholder engagement (complaint and redress channels, responsible vulnerability disclosure) and society and sustainability (protection of minors, cultural alignment, frugal AI and environmental impact assessment). A self-assessment tool scores organisational readiness out of 100 and AI system trustworthiness out of 380, and regulatory sandboxes aligned with OECD, ISO and ITU standards allow controlled testing. Privacy by design and strict conformity with the PDPL (Law No. 151 of 2020) are required throughout.
Organisations must establish clear governance structures to oversee AI use, with a CAIO or committee responsible for policies, risk management, data protection and transparency.
AI systems must be inventoried and classified by risk level from Tier 1 to Tier 4, with reinforced requirements for high-risk systems such as large language models and generative AI.
A formal, documented assessment of potential impacts on individuals, social groups and society must be integrated from the earliest lifecycle phases, covering discrimination, privacy and societal risks.
Systems must pass pre-deployment testing (Test, Evaluate, Verify, Validate) including adversarial and bias testing, and adopt HITL, HOTL or HOOTL human-oversight models proportionate to risk, with continuous post-deployment monitoring.
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AI systems processing personal data must comply strictly with Law No. 151 of 2020, with privacy by design, data minimisation and security embedded from conception.