Practical requirements extracted from policy instruments, with the source article, the actors they bind, evidence examples and original framework mappings. Legal requirements are marked; everything else is voluntary guidance.
High-risk AI systems must achieve an appropriate level of accuracy, robustness and cybersecurity and perform consistently throughout their lifecycle. Accuracy levels and metrics must be declared in the instructions; systems must be resilient to errors, faults and inconsistencies, address feedback loops in continuously learning systems, and resist attempts to alter use or performance, including data poisoning, model poisoning, adversarial examples and confidentiality attacks.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementData governance and quality·European Union
High-risk AI systems that use data-driven techniques must be developed on training, validation and testing data sets meeting quality criteria: appropriate governance practices covering design choices, data collection and origin, preparation, assumptions, availability and suitability, examination for possible biases, and measures to detect, prevent and mitigate bias. Data must be relevant, sufficiently representative and, to the best extent possible, free of errors and complete for the intended purpose.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementData governance and quality·European Union
To the extent a deployer controls the data fed into a high-risk AI system, it must make sure that input data is relevant to, and sufficiently representative for, the system's intended purpose. The duty sits with the deployer even though the provider designed the system, because the deployer chooses what the system is run on.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementGovernance and accountability·European Union
A distributor, importer, deployer or other third party is treated as the provider of a high-risk AI system, with all Article 16 duties, if it puts its own name or trademark on a system already on the market, makes a substantial modification to a high-risk system that stays high-risk, or changes the intended purpose of a system so that it becomes high-risk. The original provider then ceases to be provider for that system but must cooperate and supply the information and access needed for the new provider to comply.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementGovernance and accountability·South Korea
Operators of high-impact AI must prepare and implement a plan to protect users, and must prepare and keep documents describing the measures they take to secure the AI's safety and reliability, so that they can be shown to the Ministry of Science and ICT on request. Further items may be added by Presidential Decree, and the ministry may publish guidelines on how to meet these duties.
Verified (a factual check against the official source, not a legal review)Applies from 22 Jan 2026
Legal requirementGovernance and accountability·European Union
Article 16 lists what a provider of a high-risk AI system owes: compliance with the Section 2 requirements, its name and contact details on the system or its documentation, a quality management system, retention of documentation and logs, conformity assessment, an EU declaration of conformity, CE marking, registration, corrective action when needed, cooperation with authorities on request, and accessibility in line with the EU accessibility directives.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementGovernance and accountability·European Union
Deployers of high-risk AI must take technical and organisational measures to use systems according to the instructions, assign human oversight, ensure input data is relevant where they control it, monitor operation, inform the provider and authorities of risks or serious incidents, keep logs, inform workers' representatives before deploying at the workplace, inform affected natural persons where decisions are made about them, and cooperate with authorities.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
ICO AI guidance · UK GDPR Article 22 as amended by the Data (Use and Access) Act 2025
Individuals have rights in relation to solely automated decisions that produce legal or similarly significant effects, including being told about the decision, obtaining human intervention, and contesting it. The Data (Use and Access) Act 2025 amended these rules; the reviewer must confirm the current wording.
Source-linked (a factual check against the official source, not a legal review)
EU AI Act · Article 14; Article 26(2) for deployers
High-risk systems must be designed with human-machine interface tools so natural persons can effectively oversee them, understand capacities and limitations, avoid automation bias, interpret output, decide not to use the system, and intervene or stop it. Deployers must assign oversight to people with the necessary competence, training and authority. For certain remote biometric identification systems, action requires verification by at least two competent persons.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
A consumer who receives an adverse consequential decision may obtain meaningful review by a person with the authority and information to change the outcome. Scope and timing follow the enrolled bill.
Pending review (a factual check against the official source, not a legal review)Applies from 1 Jan 2027
Operators of high-impact AI must ensure that the AI is subject to human management and supervision, so that people remain able to monitor its operation and intervene in or override its outputs where those outputs may affect life, physical safety or fundamental rights.
Verified (a factual check against the official source, not a legal review)Applies from 22 Jan 2026
UAE PDPL · Article on data-subject rights relating to automated processing (reviewer to cite article number)
Data subjects may object to decisions based solely on automated processing, including profiling, that produce legal or similarly serious effects, subject to exceptions such as contractual necessity or consent.
Pending review (a factual check against the official source, not a legal review)
ICO AI guidance · UK GDPR Article 35; ICO guidance, accountability and governance section
Where AI processing of personal data is likely to result in a high risk to individuals, UK GDPR requires a DPIA before processing begins. The ICO treats most AI involving profiling, large-scale processing or novel technology as meeting this threshold.
Source-linked (a factual check against the official source, not a legal review)
Before deploying most Annex III high-risk systems, deployers that are bodies governed by public law or private entities providing public services, and deployers using systems for creditworthiness assessment or life and health insurance pricing, must assess the impact on fundamental rights: the processes, period and frequency of use, categories of affected persons, specific risks of harm, human-oversight measures and mitigation, and notify the market-surveillance authority of the results.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Deployers must complete an impact assessment before deployment, annually, and within 90 days of any intentional and substantial modification, covering purpose, risks of algorithmic discrimination and mitigation, data categories, performance metrics, transparency measures and post-deployment monitoring, and retain assessments for at least three years.
Pending review (a factual check against the official source, not a legal review)
Entities notified as Significant Data Fiduciaries, based on factors such as volume and sensitivity of data and risk to individuals, must appoint a Data Protection Officer based in India, an independent data auditor, and periodically undertake data protection impact assessments and audits.
Source-linked (a factual check against the official source, not a legal review)
If a deployer discovers that a high-risk AI system it uses has caused algorithmic discrimination, it must send a notice to the Colorado Attorney General within 90 days of the discovery, in the form the Attorney General prescribes, without unreasonable delay.
Pending review (a factual check against the official source, not a legal review)
Within 90 days after a developer discovers, through ongoing testing or a credible report from a deployer, that a high-risk AI system it developed has caused or is reasonably likely to have caused algorithmic discrimination, it must disclose this to the Colorado Attorney General and to all known deployers or other developers of the system, without unreasonable delay.
Pending review (a factual check against the official source, not a legal review)
Legal requirementIncident reporting and handling·European Union
A provider that considers, or has reason to consider, that a high-risk system it has placed on the market is not in conformity must immediately correct it, withdraw it, disable it or recall it as appropriate, and inform the distributors, deployers, authorised representative and importers. Where the system presents a risk to health, safety or fundamental rights and the provider becomes aware of that risk, it must immediately investigate the causes together with the reporting deployer and inform the market surveillance authorities and, where relevant, the notified body.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Deployers must monitor a high-risk AI system's operation against the provider's instructions and feed observations to the provider under Article 72. If they have reason to think the system as used may present a risk to health, safety or fundamental rights, they must inform the provider or distributor and the market surveillance authority without undue delay and suspend use. On a serious incident, they must immediately inform the provider, then the importer or distributor and the authorities. Financial institutions meet this through their internal governance rules.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Providers must establish and document a post-market monitoring system proportionate to the nature of the AI technology and its risks, actively and systematically collecting and analysing performance data throughout the system's lifetime, based on a monitoring plan that is part of the technical documentation. The Commission is to adopt a template for the plan.
Pending review (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementPrivacy and personal-data protection·Nepal
Nepal Privacy Act 2075 · Chapter on collection and protection of personal information (reviewer to cite sections)
Personal information may be collected only by authorised persons for a lawful purpose with the individual's consent, and must not be used or disclosed for other purposes without consent, subject to statutory exceptions. AI systems trained on or processing personal data of people in Nepal must respect these limits.
Pending review (a factual check against the official source, not a legal review)
Legal requirementPrivacy and personal-data protection·European Union
Where a deployer of a high-risk AI system is required to carry out a data protection impact assessment under Article 35 of the GDPR or Article 27 of the Law Enforcement Directive, it must draw on the information the provider supplied under Article 13, such as the intended purpose, performance, limitations and human-oversight measures, when producing that assessment.
Verified (a factual check against the official source, not a legal review)Applies from 2 Dec 2027
Legal requirementPrivacy and personal-data protection·Singapore
PDPC AI advisory guidelines · Advisory guidelines, sections on consent, business improvement and research exceptions
Personal data used to train or operate AI systems requires consent unless an exception applies, such as the business improvement exception for improving products and services or the research exception for developing models, each subject to conditions.
Source-linked (a factual check against the official source, not a legal review)
Legal requirementPrivacy and personal-data protection·India
Personal data may be processed only for a lawful purpose with the individual's free, specific, informed and unambiguous consent, or for certain legitimate uses listed in the Act. A notice must describe the data, purpose, and how to exercise rights and complain.
Source-linked (a factual check against the official source, not a legal review)
A single practical requirement pulled out of an instrument and stated on its own: keep a risk management system, log incidents, document training data, provide human oversight, and so on. Each one cites the article or section it comes from so you can check it against the source.
Does a voluntary obligation have legal force?
No, and every obligation is labelled either a legal requirement or voluntary guidance. Voluntary items still matter in practice, because procurement questionnaires and auditors ask about them, but only the binding ones carry legal consequence.
How do I find the obligations that apply to my organisation?
Filter by jurisdiction, category, actor, sector or use case. The applicability check asks a short set of questions and returns the duties that may reach you. It is an educational screen, not a legal determination, and it says so.
Why do some instruments have no obligations listed?
Because nobody has broken them out yet. Most instruments are recorded at summary level first; obligations are added jurisdiction by jurisdiction. The coverage and open-gaps pages publish exactly what is missing rather than hiding it.
