🔴Illinois HB 3773IN EFFECTUp to ~$70K/violation|🔴Texas TRAIGA (HB 149)IN EFFECTAG-enforced|🔴Utah AI Policy ActIN EFFECT$2,500/violation|⚠️Colorado AI Act (SB 205)Jan 1, 2027AG-enforced|⚠️California SB 942Aug 2, 2026$5K/day|⚠️EU AI Act Art. 50Aug 2, 2026€35M or 7% revenue|⚠️New York RAISE ActJan 1, 2027AG civil penalties|
European Union · EU AI ActNo AI-specific law — data-protection law binds

Qatar AI Compliance Requirements

Mandatory and recommended controls under EU AI Act + national rules, including the role of the local data-protection authority.

Deadline: No AI-specific deadline. The Personal Data Privacy Protection Law has been in force since 2016; Council of Ministers Decision No. 1 of 2018 extended the compliance grace period for those it addresses.Penalty: No AI-specific penalty exists. The binding exposure is the PDPPL's Chapter Seven, read from the register's own text of the Act: Article 23 sets a fine of up to QAR 1,000,000 for breaching Articles 4, 8–12, 14, 15 or 22; Article 24 up to QAR 5,000,000 for Articles 13, 16 (third paragraph) or 17; Article 25 fines a legal person up to QAR 1,000,000 where an offence is committed in its name and for its account, without prejudice to the criminal liability of the natural person responsible.

How AI law works in Qatar

Qatar has no AI statute, and that is a measurement rather than a summary: Al Meezan — the Ministry of Justice's register of everything enacted since 1961 — returns exactly ONE instrument for الذكاء الاصطناعي, and it is Council of Ministers Decision No. 10 of 2021, which establishes an Artificial Intelligence Committee inside the Ministry of Transport and Communications. Its eleven articles are institutional throughout — membership, three-year terms, monthly meetings, quarterly reporting to the Minister, and a remit under Article 3 to implement and monitor Qatar's National AI Strategy. It creates no obligation on anyone deploying an AI system and contains no penalty provision of any kind (verified against the full text: no عقوبة, غرامة, يعاقب, حبس or ريال anywhere in it, and its single prohibition in Article 8 is a confidentiality duty on the committee's own members). What actually binds a business using AI in Qatar is Law No. 13 of 2016 on the Protection of Personal Data Privacy — the first comprehensive data-protection law in the GCC, in force since 3 November 2016 and administered by the Ministry of Communications and Information Technology — together with Decree-Law No. 16 of 2010 on Electronic Commerce and Transactions. The PDPPL requires a lawful basis and prior consent for processing, imposes duties of transparency, purpose limitation, accuracy and security, gives individuals rights of access, correction, erasure and objection, requires prior permission from the competent department before processing data of special nature (health, ethnicity, religion, criminal records, children), and requires prior consent before sending electronic direct-marketing communications.

Applicable laws

  • 📜 قانون رقم (13) لسنة 2016 بشأن حماية خصوصية البيانات الشخصية — Law No. 13 of 2016 on the Protection of Personal Data Privacy
  • 📜 قرار مجلس الوزراء رقم (10) لسنة 2021 بإنشاء لجنة الذكاء الاصطناعي — Council of Ministers Decision No. 10 of 2021 establishing the Artificial Intelligence Committee
  • 📜 مرسوم بقانون رقم (16) لسنة 2010 بإصدار قانون المعاملات والتجارة الالكترونية — Decree-Law No. 16 of 2010 on Electronic Commerce and Transactions
  • 📜 Qatar National Artificial Intelligence Strategy (2019, policy)

EU AI Act requirements begin with system risk assessment. Your organization must evaluate every AI system against the EU AI Act's risk framework: prohibited systems (facial recognition in law enforcement, social credit scoring, subliminal manipulation), high-risk systems (hiring, benefits determination, law enforcement, biometric ID), limited-risk systems (chatbots), and minimal-risk systems (game AI, spam filters). The legal requirement is to classify your system correctly. Misclassification — for example, claiming that a hiring AI is minimal-risk when it is high-risk — is itself a compliance violation. High-risk classification triggers the heaviest compliance burden: conformity assessment, bias and fairness testing, documented risk mitigation, human oversight, transparency, and record-keeping. If you are uncertain whether a system is high-risk, the safe assumption is to treat it as high-risk and apply the full compliance framework.

Pre-deployment conformity assessment is the core requirement for high-risk systems. Before deploying a high-risk AI system (or immediately, if it is already deployed), you must complete a documented assessment covering: data quality — are the training and decision-making data representative of the population affected by the system, and do they contain known biases?; model performance — does the model perform equally well across demographic groups, or is accuracy lower for protected groups?; system explainability — can you explain to an affected individual why the system made a particular decision?; human oversight design — what process allows an individual to escalate the AI decision to human review?; and risk mitigation — what controls have you implemented to reduce the risk of discriminatory outcomes? This assessment must be documented in writing, reviewed by qualified personnel, and updated at least annually.

Bias and fairness testing is a specific requirement for high-risk systems. The EU AI Act does not prescribe a particular testing methodology, but requires that your organization conduct documented testing and be able to demonstrate that you have evaluated the system for discriminatory impact across protected characteristics (race, color, religion, national origin, sex, gender identity, sexual orientation, disability, age, etc.). Testing must include: hold-out test data not used in training, representative of the affected population; evaluation of decision-rate parity across groups (does the AI approve loans at the same rate for all genders, races, and age groups?); and performance parity testing (does the AI make accurate predictions equally well across all groups?). Document test results, identify any disparate impact, and implement mitigation (rebalance training data, adjust decision thresholds, redesign features, or limit the system's scope).

Transparency and human-rights mechanisms are mandatory for all systems, with intensity scaling to risk level. For limited-risk systems (chatbots), you must disclose that the individual is interacting with AI. For high-risk systems, transparency is much deeper: you must inform affected individuals before the AI system makes a decision about them, explain what data the system is using, describe how the system works (at a non-technical level accessible to the individual), and provide the individual with a clear, accessible process to request human review and appeal the AI decision. In employment and benefits contexts, individuals must be able to request re-evaluation by a human reviewer, and that human review must be genuine — a human who has authority to override the AI decision and the information needed to make an independent judgment.

Ongoing monitoring, record-keeping, and individual-rights response are permanent obligations. You must monitor every high-risk AI system's performance and decisions on an ongoing basis (not just at deployment). Maintain audit logs of every high-risk decision for at least three years, capturing inputs, decision outputs, confidence scores, human-review flags, and any human override. When an individual requests an explanation of an AI decision, you must respond within 30 days with accessible, non-technical information about how the system works and why it made that particular decision. When an individual requests appeal or human review, you must provide it. Failure to respond to individual rights requests is a documented compliance violation and a source of private civil liability.

Qatar compliance requirements, ranked

Mandatory under EU AI Act + GDPR

Risk classification per national framework + GDPR-equivalent DPIA
Public AI-use disclosure to end-users in their language
Human review path for adverse automated decisions (GDPR Art. 22)
Cooperation with Qatar's supervisory authority + serious-incident reporting
Records sufficient to reconstruct each automated decision (3+ years)

Strongly recommended

Annual third-party bias / fairness audit
AI vendor due-diligence questionnaire (training data provenance, sub-processors, retention)
Cross-functional AI governance committee
Public-facing complaint mechanism

Country context

Applicable framework: قانون رقم (13) لسنة 2016 بشأن حماية خصوصية البيانات الشخصية — Law No. 13 of 2016 on the Protection of Personal Data Privacy
Applicable framework: قرار مجلس الوزراء رقم (10) لسنة 2021 بإنشاء لجنة الذكاء الاصطناعي — Council of Ministers Decision No. 10 of 2021 establishing the Artificial Intelligence Committee
Applicable framework: مرسوم بقانون رقم (16) لسنة 2010 بإصدار قانون المعاملات والتجارة الالكترونية — Decree-Law No. 16 of 2010 on Electronic Commerce and Transactions
Applicable framework: Qatar National Artificial Intelligence Strategy (2019, policy)
Regulator: see official sources block below for Qatar's primary AI / data-protection authority.
Status: No AI-specific law — data-protection law binds. Headline penalty exposure: No AI-specific penalty exists. The binding exposure is the PDPPL's Chapter Seven, read from the register's own text of the Act: Article 23 sets a fine of up to QAR 1,000,000 for breaching Articles 4, 8–12, 14, 15 or 22; Article 24 up to QAR 5,000,000 for Articles 13, 16 (third paragraph) or 17; Article 25 fines a legal person up to QAR 1,000,000 where an offence is committed in its name and for its account, without prejudice to the criminal liability of the natural person responsible..

More Qatar resources

AI Compliance Checklist💰 AI Law Fines & Penalties📖 AI Compliance Guide AI Law Deadlines← All Qatar resources

Other countries

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Editorial standards

Anchored to the primary government source (statute, bill text, or agency rule) and verified directly against it · Last verified Aug 31, 2026. See our methodology.

Primary sources · Qatar
  • almeezan.qahttps://www.almeezan.qa/LawPage.aspx?id=7121&language=ar
  • almeezan.qahttps://www.almeezan.qa/LawPage.aspx?id=8719&language=ar
  • almeezan.qahttps://www.almeezan.qa/LawPage.aspx?id=2678&language=ar