Qatar - AI Security Guidelines
Guidelines for Secure Adoption and Use of Artificial Intelligence
Guidelines for Secure Adoption and Use of Artificial Intelligence (National Cyber Security Agency)
Qatar
RAI-QA-NA-GSAUAXX-2024Qatar - AI Security Guidelines is In Force in Qatar, according to ncsa.gov.qa. We have not yet been able to confirm the status.
GuidelineGovernance and OversightRisk ManagementCybersecurity and Model SecurityThe National Cyber Security Agency (NCSA) of Qatar published the bilingual "Guidelines for Secure Adoption and Usage of Artificial Intelligence" (Version 1.0) in February 2024 to help public and private organisations adopt AI securely. The voluntary guidance focuses on people, processes and technology across the AI lifecycle and offers risk-management, security controls, governance and testing recommendations. (ncsa.gov.qa)
Summary
Background and purpose: In February 2024 the National Cyber Security Agency (NCSA) published Version 1.0 of the "Guidelines for Secure Adoption and Usage of Artificial Intelligence" to provide a practical, security-focused framework for organisations in Qatar that deploy or operate AI systems. The guidance is bilingual (Arabic/English), prepared by NCSA specialists, and was launched alongside a multi-stakeholder conference in Doha. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Scope and nature of the instrument: The Guidelines are explicitly published as guidance (not as a statutory regulation) and are designed to be practical and sector-neutral. They apply to public and private sector organisations operating in Qatar and to systems that process or infer information about individuals, the organisation, or national critical infrastructure. The document references NCSA’s mandate under the Amiri decree establishing the Agency and positions cybersecurity as an enabler of trustworthy AI deployment. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Core approach: The NCSA guidance is organized around the classic triad of people, process and technology and follows the AI lifecycle (from planning and design to deployment, monitoring and decommissioning). It emphasizes strategic requirements for AI adoption (why AI is needed, selection and validation of solutions, security engineering, and verification), and includes recommended controls for data protection, model security, supply chain oversight, access control, logging and human oversight for high‑impact functions. The guidance also highlights generative AI-specific risks (e.g., data leakage, hallucinations) and proposes mitigations. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Risk and compliance bearings: Although voluntary, the Guidelines are intended to influence procurement, internal governance, and sectoral regulators. NCSA and other national stakeholders may use the framework as a baseline for future mandatory measures or sectoral requirements; for example, financial regulators in Qatar moved in 2024 to issue mandatory AI controls for banking entities. Organisations are recommended to integrate the guidance into existing security and privacy management systems and to document compliance, validation and incident handling procedures. ([crowell.com](https://www.crowell.com/en/insights/client-alerts/the-middle-easts-big-bet-on-artificial-intelligence-and-data-security?utm_source=openai))
Practical outputs: The Guidelines provide checklists, recommended practices for testing and evaluation, model documentation templates, incident reporting expectations, and governance roles and responsibilities (including C-suite oversight, privacy officers and security owners). They also set out monitoring and evaluation expectations and encourage alignment with international standards and frameworks. Overall the document functions as an operational bridge between Qatar’s national AI strategy and organisational cybersecurity practice. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Full article
Read full text ↗Overview
The "Guidelines for Secure Adoption and Usage of Artificial Intelligence" (NCSA, Version 1.0, Feb 2024) is a practical, bilingual (Arabic/English) guidance manual published by the National Cyber Security Agency of Qatar to help organisations adopt AI securely and responsibly. It was launched during an NCSA conference on the safe use of AI in Doha in February 2024 and is positioned as a national baseline for risk‑aware AI deployment. The document structures recommendations around people, processes and technology and maps controls to the AI lifecycle (design, development, deployment, monitoring and decommissioning). The full NCSA publication is available from the Agency's repository (see Guidelines PDF (NCSA)) and NCSA has emphasised that cybersecurity should be treated as an enabler of innovation rather than a blocker. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Definitions
The Guidelines define key terms used throughout the document, including: "AI system" (the software and related components implementing automated inference/prediction/decision functions), "deployers" (organisations that put AI into production), "providers" (third‑party model/API vendors), "high‑risk AI" (systems whose failure could materially affect safety, fundamental rights or critical infrastructure), "model security" (measures to prevent theft, poisoning, extraction and misuse), and "human oversight" (designs ensuring meaningful human control over significant outcomes). Definitions aim to be technology‑agnostic and to align with accepted international vocabularies to ease cross‑jurisdictional alignment. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Governance and Institutional Framework
The Guidelines place organisational governance at the centre of secure AI adoption. NCSA recommends establishing a formal governance structure including executive sponsorship (board/C‑suite visibility), a designated AI governance lead, cross‑functional risk committees, and clear role definitions for security, legal/privacy, and business owners. They advise that governance mechanisms should integrate with existing enterprise risk management, data protection and cybersecurity programmes rather than operate in silos. The guidance also notes NCSA’s institutional role and points to coordination with national AI policy bodies such as the Ministry of Communications and Information Technology and the Artificial Intelligence Committee (MCIT AI Committee) when policies or sectoral rules interact. NCSA further identifies critical infrastructure owners as priority partners for targeted interventions. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Key Focus Areas
The Guidelines identify a set of key focus areas that organisations should manage across the AI lifecycle: 1) Strategic alignment and justification (clear business or public service objectives for AI use); 2) Risk assessment and classification (system categorisation by impact); 3) Data governance and privacy (data minimisation, lawful basis, anonymisation where appropriate); 4) Model security and integrity (anti‑poisoning, access controls, provenance); 5) Robustness, testing and evaluation (adversarial testing, performance validation across operational conditions); 6) Explainability and transparency (user‑facing disclosures, model cards); 7) Human oversight and escalation procedures (human‑in‑the‑loop for critical decisions); 8) Supply chain and third‑party risk management (contracts, SLAs, security requirements for API/model providers); 9) Monitoring, logging and incident response (observability, telemetry, forensics readiness); and 10) Continuous improvement and decommissioning plans. The document includes recommended technical and organisational controls tailored to each area and emphasizes documentation and evidence as core deliverables. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Implementation Framework
NCSA provides an implementation blueprint that organisations can adapt: start with a governance and scoping phase (inventory systems, classify risk), move to design and procurement (security requirements, privacy impact assessments, procurement checklists), proceed to secure development and validation (secure coding, data lineage, model testing), then to controlled deployment (staged rollout, monitoring), and finally to operations and decommissioning (incident management, retention policies). Each stage includes recommended artifacts: risk registers, model documentation (technical model cards and decision logs), test reports, and third‑party assurance records. The Guidance encourages integration with existing ISO/NIST controls and to adopt a principle of least privilege, immutable logging and reproducible model pipelines. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Monitoring and Evaluation
Operational monitoring is emphasized as critical for safety and security. The Guidelines recommend continuous telemetry (performance, drift, anomalous inputs), scheduled revalidation (retests against fresh datasets), and escalation thresholds for when human review, rollback or model retraining is required. They also prescribe post‑deployment audits, periodic privacy impact assessments, and reporting mechanisms for incidents involving data leaks, model misuse or material errors. NCSA encourages organisations to create internal KPIs for AI safety and security and to share anonymised lessons learned with national authorities to strengthen the ecosystem. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Penalties, Liability, and Appeals
Because the document is published as guidance, it does not itself create administrative fines or criminal penalties; however, NCSA warns that failure to follow recommended practices may expose organisations to legal, contractual and regulatory consequences under existing laws (e.g., data protection or sectoral rules). The Guidelines recommend contractual clauses to allocate liability with providers, clear incident reporting timelines, and documented remediation steps. NCSA states that the guidance may inform future mandatory measures and that affected entities should track sectoral regulators (for example, financial sector regulators have since adopted mandatory AI requirements). The document describes dispute‑resolution best practices and appeals channels where sectoral regulators are involved. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Relationship to Other Instruments
The Guidelines are presented as complementary to Qatar’s National AI Strategy (MCIT) and to existing cybersecurity and data protection instruments. NCSA states the Guidance takes into account national legal frameworks and may be used with international standards (e.g., NIST AI RMF, ISO standards) to achieve interoperability and benchmarked assurance. The document references the NCSA legal mandate (Amiri Decree establishing NCSA) and positions the Guidance as an operational bridge between national AI policy objectives and organisational controls. Organisations are advised to reconcile the Guidance with sectoral rules (e.g., banking, healthcare) where mandatory regimes apply. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
International Alignment
The Guidelines explicitly encourage alignment with leading international frameworks and good practices to facilitate cross‑border interoperability and procurement. NCSA calls for adoption of internationally recognised standards for testing, model documentation and risk assessment, and for participation in international fora to share experience and incidents. The Guidance notes international developments (e.g., regulator approaches in other jurisdictions) and promotes harmonisation to reduce fragmentation for global suppliers. NCSA also highlights sectoral coordination with bodies such as the Ministry of Communications and Information Technology as part of international cooperation efforts. ([ncsa.gov.qa](https://ncsa.gov.qa/sites/default/files/2024-02/AI-Guide-en-V6.pdf))
Implementation Timeline
| Milestone | Recommended Timing |
|---|---|
| Publish & national launch | Feb 2024 (NCSA launch conference) |
| Organisational scoping and inventory | 0–3 months after publication |
| Risk classification and governance set‑up | 1–6 months |
| Procurement & contractual safeguards | 3–9 months |
| Validation, testing, and pilot deployment | 3–12 months |
| Operational monitoring & audits | Ongoing after deployment |
Sources and References
| Source | Type |
|---|---|
| Guidelines for Secure Adoption and Usage of Artificial Intelligence (NCSA, Feb 2024) | Primary Source |
| NCSA launches guidelines for secure adoption and use of AI (The Peninsula) | Secondary/Press |
| MCIT — Artificial Intelligence Committee / National AI Strategy references | Related Primary Source |
Requirements for a company
What an organisation has to do under Qatar - AI Security Guidelines, at a glance. Not legal advice — the table below gives the provision and deadline for each item.
Must do
15- Reconcile AI guidance with mandatory sectoral rules.Organisations in regulated sectors.
- Implement data governance for AI, ensuring data minimisation and lawful basis.Organisations adopting AI.
- Perform Privacy Impact Assessments for AI systems.Organisations adopting AI.
- Inventory all AI systems and classify their risks.Organisations adopting AI.
- Establish a formal AI governance structure with executive sponsorship and clear roles.Organisations adopting AI.
- Conduct risk assessment and classify AI systems by impact.Organisations adopting AI.
- +9 more in the table below
Must not do
0Nothing in this category.
Should do
0Nothing in this category.
Should not do
0Nothing in this category.
Who must do what
The obligations under Qatar - AI Security Guidelines, most serious first. Not legal advice — verify against the official text before relying on it.
| # | Who | Requirement | By when | Where | Severity |
|---|---|---|---|---|---|
| 1 | Organisations in regulated sectors. | Reconcile AI guidance with mandatory sectoral rules. “Organisations are advised to reconcile the Guidance with sectoral rules (e.g., banking, healthcare) where mandatory regimes apply.” | — | Relationship to Other Instruments | Critical |
| 2 | Organisations adopting AI. | Implement data governance for AI, ensuring data minimisation and lawful basis. “Data governance and privacy (data minimisation, lawful basis, anonymisation where appropriate)” | — | Key Focus Areas | Critical |
| 3 | Organisations adopting AI. | Perform Privacy Impact Assessments for AI systems. “privacy impact assessments” | Before placing on market | Implementation Framework | Critical |
| 4 | Organisations adopting AI. | Inventory all AI systems and classify their risks. “start with a governance and scoping phase (inventory systems, classify risk)” | May 18, 2024 | Implementation Framework | Important |
| 5 | Organisations adopting AI. | Establish a formal AI governance structure with executive sponsorship and clear roles. “NCSA recommends establishing a formal governance structure including executive sponsorship...” | Aug 18, 2024 | Governance and Institutional Framework | Important |
| 6 | Organisations adopting AI. | Conduct risk assessment and classify AI systems by impact. “Risk assessment and classification (system categorisation by impact)” | Aug 18, 2024 | Key Focus Areas | Important |
| 7 | Organisations adopting AI. | Manage supply chain and third-party risks for AI, including contractual safeguards. “Supply chain and third‑party risk management (contracts, SLAs, security requirements for API/model providers)” | Nov 18, 2024 | Key Focus Areas | Important |
| 8 | Organisations procuring AI systems. | Include contractual clauses to allocate liability with AI providers. “The Guidelines recommend contractual clauses to allocate liability with providers” | Nov 18, 2024 | Penalties, Liability, and Appeals | Important |
| 9 | Organisations adopting AI. | Conduct robust testing and evaluation of AI systems, including adversarial testing. “Robustness, testing and evaluation (adversarial testing, performance validation across operational conditions)” | Feb 18, 2025 | Key Focus Areas | Important |
| 10 | Organisations deploying AI. | Implement continuous monitoring, logging, and incident response for AI systems. “Monitoring, logging and incident response (observability, telemetry, forensics readiness)” | Ongoing after deployment | Key Focus Areas | Important |
| 11 | Organisations adopting AI. | Maintain documentation and evidence of AI system controls and processes. “emphasizes documentation and evidence as core deliverables.” | — | Key Focus Areas | Important |
| 12 | Organisations adopting AI. | Ensure explainability and transparency for AI systems, including user disclosures and model cards. “Explainability and transparency (user‑facing disclosures, model cards)” | — | Key Focus Areas | Important |
| 13 | Organisations adopting AI. | Integrate AI governance with existing enterprise risk management and cybersecurity programs. “They advise that governance mechanisms should integrate with existing enterprise risk management, data protection and cybersecurity programmes.” | — | Governance and Institutional Framework | Important |
| 14 | Organisations adopting AI. | Implement security measures to protect AI models from poisoning, theft, and misuse. “Model security and integrity (anti‑poisoning, access controls, provenance)” | — | Key Focus Areas | Important |
| 15 | Organisations deploying AI. | Establish human oversight and escalation procedures for critical AI decisions. “Human oversight and escalation procedures (human‑in‑the‑loop for critical decisions)” | — | Key Focus Areas | Important |
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