EU AI Act Explained: Obligations, Risk Tiers & Who It Applies To

Author: Derrick D. Jackson

Title: Founder & Senior Director of Cloud Security Architecture & Risk
Credentials: CISSP, CRISC, CCSP
Last updated: August 10th, 2025

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This EU AI ACT guide explains Regulation (EU) 2024/1689—the EU Artificial Intelligence Act—its purpose, scope, and who must comply.

Verify in Official Journal (EU AI Act)

Navigating the EU AI Act doesn’t have to be overwhelming. Whether you’re a CTO planning your AI strategy(Complete AI governance framework), a compliance officer ensuring regulatory alignment, or simply curious about how Europe’s groundbreaking AI regulation affects your organization, this comprehensive guide breaks down everything you need to know. From understanding the Act’s four-tier risk framework to identifying your specific obligations and deadlines, we’ll walk you through the practical steps to achieve compliance while continuing to innovate. You’ll discover how the regulation impacts different roles within your organization, learn which AI systems are prohibited versus those requiring special safeguards, and gain actionable insights to build a compliant AI governance framework that protects both your business and the fundamental rights of EU citizens.

The Act lays down harmonized rules for placing AI systems on the EU market (Art. 1).
Verify Subject Matter: Article 1

Beginner

Essential basics for first-time learners. Understand what the EU AI Act is and if it affects you or your business.

What is the EU AI Act

Who does it affect? When do requirements kick in? Why should you care? How to get started 15 minutes

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Intermediate

Efficient implementation strategies and optimal compliance approaches for your organization.

Implementation Roadmaps

Resource allocation strategies Efficient compliance processes Team coordination methods Quick wins and priorities

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Advanced

Monitor compliance, measure effectiveness, optimize processes, and automate where possible.

Compliance monitoring systems

Performance measurement tools Process optimization techniques Automation opportunities Continuous improvement methods

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EU AI ACT Article Tracker

EU AI ACT Risk Categories

What is the EU AI Act? by Lisa Yu

The Act establishes different risk categories through Articles 5 (prohibited practices), 6 (high-risk classification), and 50 (transparency obligations), which are commonly interpreted as a four-tier framework.

Prohibited AI Systems Under the EU AI Act

The EU AI Act prohibits the following categories of AI systems:

Behavioral Manipulation AI systems that manipulate human behavior to circumvent users’ free will, such as toys using voice assistance encouraging dangerous behavior of minors.

Social Scoring Systems that allow social scoring by governments or companies.

Predictive Policing Certain applications of predictive policing.

Biometric Systems

Article 5(1)(h) on biometric identification

Emotion recognition systems used at the workplace
Some systems for categorizing people
Real-time remote biometric identification for law enforcement purposes in publicly accessible spaces (with narrow exceptions)

Discrimination and Exploitation AI systems that discriminate against individuals or exploit their vulnerabilities.

Penalties and Timeline
Article 99: Penalties

Violations in this category carry the highest fines under the Act: up to €35 million or 7% of global annual turnover, whichever is higher.

Prohibitions for these systems apply six months after the AI Act’s entry into force, which is February 2, 2025.

High-Risk AI Systems Under the EU AI Act

Article 6: Classification Rules for High-Risk AI Systems

High-risk AI systems are subject to stringent requirements because they pose significant risks to health and safety or fundamental rights.

Classification Criteria

The AI Act identifies high-risk systems through two main categories:

1. AI as Safety Components (Annex I) AI systems intended to be used as a safety component of a product, or where the AI system is itself a product, covered by specific EU harmonization legislation including:

Medical devices
Toys
Machinery
Vehicles
Civil aviation
Lifts
Radio equipment

This classification applies when the product incorporating the AI system requires third-party conformity assessment under that legislation.

2. Specific Use Cases (Annex III) AI systems used in the following sensitive areas:

Critical infrastructure: Traffic, electricity, gas, water management
Medical devices
Employment and worker management: Evaluating job applications, making decisions about promotions
Education and vocational training: Determining access to institutions, evaluating learning outcomes, detecting cheating
Law enforcement: Risk assessment of criminal offenses, reliability of evidence, profiling
Migration, asylum, and border control: Polygraphs, risk assessment for entry/visa/asylum
Administration of justice and democratic processes
Access to essential services: Healthcare, social security, creditworthiness, insurance
Biometric systems: Identification, categorization, and emotion recognition (with exceptions for verification or cybersecurity purposes)

AI systems under Annex III are always considered high-risk if they perform profiling of individuals.

Requirements for Providers

Providers of high-risk AI systems must:

Implement a continuous risk management system throughout the AI system’s lifecycle
Ensure data governance for training/validation/testing datasets
Draw up technical documentation
Enable record-keeping (logs)
Provide instructions for use to deployers
Allow for human oversight
Achieve appropriate levels of accuracy, robustness, and cybersecurity
Establish a quality management system
Perform a conformity assessment
Register the system in a central EU database

The Act provides Obligations of Deployers of High-Risk AI Systems (Art. 26).
Article 26: Obligations of Deployers of High-Risk AI Systems
(Link to our services that can help guide you on your Risk Management): AI Governance & Risk Management solutions

Penalties and Timeline

Fines for non-compliance: up to €15 million or 3% of global revenues.

Implementation timeline:

Annex III systems: Obligations apply after 24 months (August 2, 2026)
Annex I systems: Obligations apply after 36 months (August 2, 2027)

Limited Risk AI Systems Under the EU AI Act

Limited risk AI systems are subject to lighter transparency obligations, primarily requiring developers and deployers to ensure that end-users are aware they are interacting with AI.

Examples of Limited Risk Systems

Chatbots
Deepfakes and other AI-generated content – must be labeled as such
Emotion recognition systems or biometric categorization systems – users must be informed of their operation

Key Requirement

The primary obligation for limited risk systems is transparency: users must know when they’re interacting with AI rather than human-generated content or human operators.

Minimal Risk AI Systems Under the EU AI Act

Most AI systems fall into this category and are unregulated by the Act, presenting minimal or no risk to citizens’ rights or safety.

Examples of Minimal Risk Systems

AI-enabled recommender systems
Spam filters

Companies may voluntarily commit to additional codes of conduct for these AI systems.

General-Purpose AI (GPAI) Models Under the EU AI Act

General-Purpose AI (GPAI) Models Under the EU AI Act

The AI Act introduces dedicated rules for GPAI models, which are capable of performing a wide range of distinct tasks and are typically trained on large amounts of data.

Dedicated rules for GPAI models are in Arts. 54–56.
Article 54: Authorized Representatives of Providers of General-Purpose AI Models

Requirements for All GPAI Model Providers

Provide technical documentation (including training and testing processes and evaluation results)
Provide information and documentation for downstream providers to help them understand capabilities and limitations
Establish a policy to comply with Union copyright law
Publish a sufficiently detailed summary about the content used for training

Free and Open-Source GPAI Models Subject to lighter regulation – only need to comply with copyright and publish the training data summary, unless they present a systemic risk.

GPAI Models with Systemic Risk

These models face additional binding obligations due to their high-impact capabilities (cumulative training compute exceeding 10^25 FLOPs or determined by Commission decision based on Annex XIII criteria).

Additional requirements:

Perform model evaluation, including conducting and documenting adversarial testing to identify and mitigate systemic risks
Assess and mitigate possible systemic risks at the Union level
Track, document, and report serious incidents and possible corrective measures to the AI Office and national competent authorities without undue delay
Ensure adequate cybersecurity protection for the model and its physical infrastructure

Timeline Obligations for GPAI systems apply after 12 months (August 2, 2025).

WHAT THE EU AI ACT MEANS FOR YOU

Expand the role below, to learn more about how the EU AI ACT can shape responsibilities.

Chief AI / Technology Officer (CTO / CAIO)

Core Concerns Under the EU AI Act: As the strategic lead for AI implementation, you're accountable for ensuring your organization's entire AI portfolio complies with the Act's risk-based framework. Your primary concerns include establishing governance structures that align AI development with organizational risk tolerance and ethical principles. You must oversee compliance across all risk categories, from prohibited systems to GPAI models with systemic risk.

Key responsibilities include implementing continuous risk management systems for high-risk AI, ensuring technical documentation and conformity assessments are completed, and maintaining the central EU database registrations. You're also responsible for AI education strategies and preventing shadow AI usage. For GPAI models, you must ensure compliance with copyright law, training data transparency, and additional obligations for systemic risk models (including adversarial testing and cybersecurity measures). Your role requires balancing innovation with regulatory compliance while fostering an appropriate organizational culture around responsible AI use.

Get guidance via our article: Operationalizing our 8-stage AI Governance Framework

Product / Solution Owner

Core Concerns Under the EU AI Act: Your role centers on ensuring AI systems meet their intended purpose while complying with the Act's requirements. You must validate that AI use cases align with business objectives without crossing into prohibited categories. For high-risk systems, you're accountable for approval decisions, ensuring models meet performance and fairness criteria before deployment. Transparency is crucial—you must ensure users know when they're interacting with AI (chatbots, deepfakes, emotion recognition systems). You participate in decision tollgates throughout the AI lifecycle, documenting system purposes, uses, and risks.

Key concerns include defining clear technical specifications, ensuring systems don't manipulate behavior or discriminate, and verifying compliance with sector-specific regulations. For systems using GPAI models, you must understand their capabilities and limitations through provider documentation. Your decisions directly impact whether AI systems require conformity assessments, database registration, or specific transparency measures based on their risk classification.

ML / Data-Science Lead

Core Concerns Under the EU AI Act: You're at the technical forefront of ensuring AI systems meet the Act's stringent requirements for accuracy, robustness, and cybersecurity. For high-risk systems, you must implement comprehensive data governance for training, validation, and testing datasets, ensuring data quality and representativeness while preventing errors. Your responsibilities include identifying and mitigating biases, implementing secure coding practices, and maintaining detailed technical documentation. For GPAI models with systemic risk, you must conduct adversarial testing and model evaluations.

Key concerns include version control, dependency tracking, and automated integrity checks. You're responsible for implementing human oversight capabilities and ensuring systems achieve appropriate performance levels. The Act requires you to document the entire development process, including hyperparameter tuning and model training procedures. You must also verify user instructions through testing and apply explainable AI techniques where needed, particularly for high-risk applications in employment, law enforcement, or essential services.

Legal & Compliance Counsel

Core Concerns Under the EU AI Act: Your role is fundamental in navigating the Act's complex legal landscape and ensuring organizational compliance across all AI systems. You must advise on risk classifications, determining whether systems fall into prohibited, high-risk, limited-risk, or minimal-risk categories. Key concerns include protecting fundamental rights, ensuring GDPR alignment, and managing contractual obligations with AI vendors. For high-risk systems, you oversee conformity assessments, CE marking requirements, and database registration obligations. You must ensure GPAI models comply with Union copyright law and training data transparency requirements.

Critical responsibilities include developing AI compliance frameworks, managing liability issues, and ensuring proper documentation for potential audits. You handle serious incident reporting obligations and coordinate with national authorities. For international deployments, you navigate cross-border compliance. Your expertise is vital in interpreting the Act's requirements, especially regarding biometric systems, profiling applications, and sector-specific regulations that trigger additional obligations.

Risk & Governance Manager / Internal Auditor

Core Concerns Under the EU AI Act: You're responsible for implementing AI-specific risk management frameworks that align with the Act's risk-based approach. For high-risk systems, you must establish continuous risk management processes throughout the AI lifecycle, systematically identifying, analyzing, and mitigating risks. Your role includes conducting regular audits to verify policy compliance and adherence to the Act's requirements.

Key concerns include assessing whether AI systems pose risks to health, safety, or fundamental rights, and ensuring appropriate mitigation measures. You develop audit frameworks to evaluate AI usage, monitor compliance with internal policies, and assess vendor risks. For GPAI models with systemic risk, you oversee the assessment and mitigation of Union-level risks. You're responsible for establishing mechanisms to track serious incidents and ensure proper reporting. Your work includes evaluating the effectiveness of human oversight measures, accuracy benchmarks, and cybersecurity protections, while ensuring trustworthy AI characteristics are integrated into organizational policies.

Procurement & Vendor-Management Lead

Core Concerns Under the EU AI Act: Your role is critical in managing supply chain risks and ensuring third-party AI products meet the Act's requirements. You must conduct thorough due diligence on vendors, verifying their compliance with relevant risk categories and obligations. For high-risk AI systems, you ensure contracts specify necessary information, capabilities, and technical access to enable compliance.

Key concerns include establishing vendor risk management programs covering security, ethical, and compliance factors. You must ensure external GPAI models provide required technical documentation, copyright compliance policies, and training data summaries. Critical responsibilities include developing standardized data usage agreements and ensuring content provenance standards. You verify that vendors of high-risk systems have completed conformity assessments and maintain proper CE marking. For AI components integrated into your products, you must ensure the supply chain maintains compliance throughout. Your work directly impacts whether your organization can demonstrate compliance when using third-party AI technologies.

MLOps / DevSecOps Engineer

Core Concerns Under the EU AI Act: You're responsible for the technical infrastructure ensuring AI systems maintain compliance throughout their operational lifecycle. For high-risk systems, you must implement automatic recording of events (logs) and ensure traceability of system functioning. Your role includes hardening MLOps pipelines, implementing automated integrity checks, and integrating security measures into CI/CD processes.

Key concerns include maintaining model accuracy, robustness, and cybersecurity protection as required by the Act. You establish continuous monitoring mechanisms to detect performance degradation or emerging risks. For GPAI models with systemic risk, you ensure adequate cybersecurity for both the model and physical infrastructure. Critical responsibilities include managing change control processes, maintaining Software Bill of Materials (SBOMs), and implementing secure deployment practices. You handle the technical aspects of serious incident detection and reporting. Your work ensures AI systems remain within their approved operational parameters and maintain required performance levels post-deployment.

Data Protection Officer (DPO)

Core Concerns Under the EU AI Act: Your role bridges GDPR and AI Act compliance, ensuring data protection throughout AI system lifecycles. You oversee how personal data is collected, processed, and stored for AI training and operations, ensuring compliance with both regulations. Key concerns include conducting Data Protection Impact Assessments (DPIAs) that complement the Act's Fundamental Rights Impact Assessments. For high-risk AI systems, you ensure data governance meets Article 10 requirements for quality, representativeness, and bias prevention. You must verify that biometric and categorization systems comply with both GDPR and the Act's specific restrictions.

Critical responsibilities include ensuring transparency in data use, implementing data minimization principles, and safeguarding individual rights. For GPAI models, you address copyright compliance and training data transparency from a privacy perspective. You manage consent requirements for AI processing and ensure appropriate legal bases. Your expertise is vital when AI systems process special categories of personal data or involve automated decision-making with legal effects.

EU AI ACT Essential Reference Tools

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EU AI ACT QMS Requirements

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EU AI Act - Article References

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EU AI ACT Glossary

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EU AI ACT Fines & Violations

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EU AI ACT Timeline Events

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EU AI ACT Risk Assessment

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Role-Based Compliance

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Documentaton & Tools Templates

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Or expand text below:

QMS Requirements

Quality Management System (QMS) Requirements Under the EU AI Act

The EU AI Act mandates comprehensive Quality Management System requirements for providers of high-risk AI systems to ensure responsible development, deployment, and management that upholds safety, transparency, accountability, and fundamental rights protection.

Purpose and Framework

The QMS must ensure compliance with the EU AI Act and establish sound quality management practices to mitigate risks and ensure trustworthiness. Documentation must be systematic and orderly, presented as written policies, procedures, and instructions.

Integration Options

Existing Products: Providers of AI systems already covered by Union harmonization legislation may integrate QMS elements into their existing quality systems, provided equivalent protection levels are achieved
Public Authorities: May implement QMS requirements within national or regional quality management systems
Microenterprises: Permitted to comply with certain QMS elements in a simplified manner

Core QMS Requirements (Quality Management System Article 17)

1. Strategy for Regulatory Compliance

Compliance with conformity assessment procedures
Processes for managing modifications to high-risk AI systems
Documentation of compliance verification methods

2. Management and Organization

Management Responsibilities: Clearly defined allocation of QMS management roles
Staff Competence: Measures ensuring personnel have necessary competence and training
Management Review: Periodic review procedures to ensure QMS suitability, adequacy, and effectiveness

3. Technical Standards and Specifications

Documentation of applied technical standards
When harmonized standards aren’t fully applicable or don’t cover all requirements, documentation of alternative compliance methods

4. Comprehensive Data Management

All data operations performed before market placement or service deployment must be documented, including:

Data Acquisition – sourcing and obtaining data
Data Collection – gathering and compiling datasets
Data Analysis – examination and evaluation procedures
Data Labeling – annotation and categorization processes
Data Storage – secure retention methods
Data Filtration – cleaning and preprocessing
Data Mining – extraction of patterns and insights
Data Aggregation – combination and synthesis
Data Retention – preservation policies and timelines

Special emphasis on ensuring training, validation, and testing datasets are relevant, representative, error-free, and complete to the best extent possible for intended purposes.

5. Documentation Requirements

Comprehensive QMS documentation
Technical documentation for each high-risk AI system
Procedures ensuring QMS remains adequate and effective
Name and address of provider
List of AI systems covered by the QMS

6. Post-Market Monitoring

Documented monitoring plan for deployed systems
Collection and review of usage experience
Identification of needs for immediate corrective or preventive actions
Continuous improvement mechanisms

7. Authority Communication

Established procedures for interacting with competent authorities
Reporting mechanisms for serious incidents
Documentation accessibility for regulatory reviews

Conformity Assessment and QMS

During conformity assessment procedures:

Providers must verify QMS compliance with Article 17 requirements
Design, development, and testing systems undergo examination and ongoing surveillance
Applications for notified body assessment must include comprehensive QMS documentation

Notified Body Requirements

Notified bodies conducting QMS assessments must satisfy:

Organizational requirements
Quality management standards
Resource adequacy
Process requirements
Cybersecurity measures

Alignment with International Standards

The EU AI Act’s QMS requirements align with broader AI governance frameworks such as ISO/IEC 42001, emphasizing:

Comprehensive risk management processes
AI impact assessments
Full lifecycle management
Continuous improvement culture

Implementation Timeline

QMS requirements apply when high-risk AI systems obligations take effect:

August 2, 2026: For most high-risk AI systems (Annex III)
August 2, 2027: For high-risk AI systems as safety components (Annex I)

Providers should begin QMS implementation well before these deadlines to ensure compliance readiness and allow time for refinement based on operational experience.

EU AI Act – Article Reference Guide

EU AI Act – Article Reference Guide Based on Regulation (EU) 2024/1689 of 13 June 2024

Chapter I: General Provisions

[Article 1: Subject Matter]: Defines the purpose of the Regulation to improve internal market functioning, promote human-centric and trustworthy AI, ensure high protection of health, safety, and fundamental rights against harmful AI effects, and support innovation.
[Article 2: Scope]: Specifies application to providers, deployers, importers, and distributors of AI systems and GPAI models within or outside the Union if output is used in the Union; excludes AI for military, defense, or national security objectives.
[Article 3: Definitions]: Provides definitions for key terms used throughout the Regulation, such as ‘AI system’, ‘provider’, ‘deployer’, ‘high-risk’, and ‘general-purpose AI model’.
[Article 4: AI Literacy]: Mandates that providers and deployers ensure sufficient AI literacy among their staff and persons dealing with AI system operation and use on their behalf.

Chapter II: Prohibited AI Practices

[Article 5: Prohibited AI Practices]: Lists strictly prohibited AI practices including systems that manipulate human behavior, exploit vulnerabilities, or use social scoring; prohibitions apply from February 2, 2025.

Chapter III: High-Risk AI Systems

Section 1: Classification

[Article 6: Classification Rules for High-Risk AI Systems]: Establishes conditions for high-risk classification including AI as safety components of products under EU harmonization legislation (Annex I) or systems used for purposes in Annex III; Commission can amend these lists.
[Article 7: Amendments to Annex III]: Grants Commission power to amend Annex III by adding or removing high-risk use cases based on criteria like risk of harm to health, safety, or fundamental rights.

Section 2: Requirements

[Article 8: Compliance with the Requirements]: States that high-risk AI systems must comply with requirements set out in this section.
[Article 9: Risk Management System]: Requires providers to establish, implement, document, and maintain continuous risk management system throughout AI system lifecycle to identify, assess, and mitigate risks.
[Article 10: Data and Data Governance]: Mandates training, validation, and testing datasets meet quality criteria emphasizing relevance, representativeness, error-freeness, and completeness to mitigate biases.
[Article 11: Technical Documentation]: Requires comprehensive technical documentation before market placement detailing design, development, data, and risk management; SMEs can provide simplified documentation.
[Article 12: Record-Keeping]: Requires automatic recording of events (logs) throughout system lifetime for traceability and post-market monitoring.
[Article 13: Transparency and Provision of Information to Deployers]: High-risk systems must include clear, comprehensive instructions enabling deployers to understand operation, functionality, strengths, and limitations.
[Article 14: Human Oversight]: Requires design and development allowing effective human oversight during use.
[Article 15: Accuracy, Robustness and Cybersecurity]: Stipulates appropriate levels of accuracy, robustness, and cybersecurity based on intended purpose and context.

Section 3: Obligations

[Article 16: Obligations of Providers of High-Risk AI Systems]: Outlines general provider obligations including ensuring compliance, quality management system, documentation, conformity assessment, EU declaration, and corrective actions.
[Article 17: Quality Management System]: Requires providers to implement documented quality management system ensuring regulatory compliance.
[Article 18: Documentation Keeping]: Providers must keep technical documentation, QMS documentation, and records available to authorities for 10 years.
[Article 19: Automatically Generated Logs]: Providers must keep logs from high-risk AI systems for at least six months when under their control.
[Article 20: Corrective Actions and Duty of Information]: Addresses corrective actions and duty to inform authorities if AI system not in conformity.
[Article 21: Cooperation with Competent Authorities]: Obliges providers to cooperate by providing necessary information and documentation upon request.
[Article 22: Authorised Representatives of Providers]: Non-EU providers must appoint EU authorized representative for compliance matters.
[Article 23: Obligations of Importers]: Importers must verify CE marking, documentation, and provider compliance before making systems available.
[Article 24: Obligations of Distributors]: Distributors must verify CE marking, documentation, and provider/importer compliance.
[Article 25: Responsibilities Along the AI Value Chain]: Clarifies when distributors, importers, deployers, or third parties become providers with provider obligations.
[Article 26: Obligations of Deployers of High-Risk AI Systems]: Deployers must use systems per instructions, monitor operation, inform affected persons, and comply with registration requirements.
[Article 27: Fundamental Rights Impact Assessment]: Public authorities and certain private entities must perform FRIA before using high-risk AI systems, identifying and mitigating fundamental rights risks.

Section 4: Notifying Authorities and Notified Bodies

[Articles 28-39]: Establish requirements for notifying authorities, conformity assessment bodies, notification procedures, operational obligations, coordination, and third-country recognition.

Section 5: Standards, Conformity Assessment, Certificates, Registration

[Article 40: Harmonised Standards and Standardisation Deliverables]: Compliance with harmonized standards published in Official Journal presumes conformity with requirements.
[Article 41: Common Specifications]: Allows common specifications to presume conformity where harmonized standards unavailable.
[Article 42: Presumption of Conformity with Certain Requirements]: Establishes specific presumptions of conformity for systems trained on representative data or certified under cybersecurity schemes.
[Article 43: Conformity Assessment]: High-risk systems require conformity assessment before market placement via internal control or notified body assessment.
[Article 44: Certificates]: Details validity periods and renewal processes for notified body certificates.
[Article 45: Information Obligations of Notified Bodies]: Notified bodies must inform authorities about issued, refused, or withdrawn certificates.
[Article 46: Derogation from Conformity Assessment Procedure]: Outlines conditions for conformity assessment derogations.
[Article 47: EU Declaration of Conformity]: Providers must draw up written declaration for each high-risk system declaring conformity with AI Act and applicable EU legislation.
[Article 48: CE Marking]: Providers must affix CE marking to systems, packaging, or documentation indicating conformity.
[Article 49: Registration]: Providers/representatives must register themselves and high-risk systems in EU database; public authorities acting as deployers also have registration obligations.

Chapter IV: Transparency Obligations

[Article 50: Transparency Obligations for Certain AI Systems]: Requires informing users they’re interacting with AI unless obvious; mandates labeling of deepfakes and AI-generated content.

Chapter V: General-Purpose AI Models

Section 1: Classification Rules

[Article 51: Classification of GPAI Models with Systemic Risk]: Defines criteria for classifying GPAI models as having systemic risk based on high-impact capabilities or compute exceeding 10^25 FLOPs; providers must notify AI Office if criteria met.
[Article 52: Procedure]: Outlines procedure for classifying GPAI models with systemic risk and maintaining list of such models.

Section 2: Obligations for Providers of General-Purpose AI Models

[Article 53: Obligations for Providers of GPAI Models]: Requires technical documentation, information for downstream providers, copyright compliance policy, and training content summary; exemptions for non-systemic risk open-source models.
[Article 54: Authorised Representatives of GPAI Providers]: Non-EU GPAI providers must appoint Union authorized representative for compliance tasks.

Section 3: Obligations for GPAI Models with Systemic Risk

[Article 55: Obligations for GPAI Models with Systemic Risk]: Additional obligations including model evaluation, adversarial testing, risk assessment/mitigation, incident reporting, and cybersecurity protection.

Section 4: Codes of Practice

[Article 56: Codes of Practice]: AI Office encourages Union-level codes covering GPAI obligations including risk management; codes should be ready by May 2, 2025.

Chapter VI: Measures in Support of Innovation

[Article 57: AI Regulatory Sandboxes]: Member States must establish at least one sandbox by August 2, 2026 to facilitate AI development and testing under regulatory oversight.
[Article 58: Detailed Arrangements for AI Regulatory Sandboxes]: Common principles for sandbox establishment and operation to avoid Union fragmentation.
[Article 59: Testing in Real World Conditions]: Allows real-world testing under specific safeguards.
[Article 60: Further Provisions for Testing in Real World Conditions]: Additional rules including required plan and EU database registration.
[Article 61: Informed Consent for Testing]: Requires documented informed consent from participants in real-world testing.
[Article 62: Measures for SMEs and Start-ups]: Member States should provide priority sandbox access and information platforms for SMEs.
[Article 63: Derogations for Specific Operators]: Allows microenterprises simplified compliance with quality management system elements.

Chapter VII: Governance

Section 1: Governance at Union Level

[Article 64: AI Office]: Establishes European AI Office within Commission to develop Union AI expertise and implement Regulation.
[Article 65: European Artificial Intelligence Board]: Establishes Board of Member State representatives for uniform application and coordination.
[Article 66: Tasks of the Board]: Board provides opinions, recommendations, and implementation guidance.
[Article 67: Advisory Forum]: Establishes stakeholder forum for input.
[Article 68: Scientific Panel of Independent Experts]: Panel provides alerts and advice on GPAI systemic risks.
[Article 69: Access to Pool of Experts]: Facilitates Member State access to expert pool.

Section 2: National Competent Authorities

[Article 70: Designation of National Competent Authorities]: Each Member State designates notifying and market surveillance authorities for supervising Regulation implementation.

Chapter VIII: EU Database

[Article 71: EU Database for High-Risk AI Systems]: Establishes central public database for registered high-risk systems with exceptions for sensitive data.

Chapter IX: Post-Market Monitoring, Information Sharing and Market Surveillance

Section 1: Post-Market Monitoring

[Article 72: Post-Market Monitoring]: Providers must establish monitoring system and plan to collect usage experience and identify corrective action needs.

Section 2: Sharing of Information

[Article 73: Reporting of Serious Incidents]: Providers must report serious incidents and corrective measures to AI Office and authorities without undue delay.

Section 3: Enforcement

[Articles 74-84]: Cover market surveillance, mutual assistance, supervision of testing, authority powers, confidentiality, procedures for risk evaluation, safeguards, compliance issues, and testing support structures.

Section 4: Remedies

[Article 85: Right to Lodge a Complaint]: Confirms right to lodge complaints with market surveillance authority.
[Article 86: Right to Explanation of Individual Decision-Making]: Grants affected persons right to clear explanation of high-risk AI decisions with legal or significant effects.
[Article 87: Reporting of Infringements]: Applies whistleblower protection directive to AI Act infringement reporting.

Section 5: Supervision of General-Purpose AI Models

[Articles 88-94]: Commission/AI Office has exclusive GPAI enforcement powers including monitoring, documentation requests, evaluations, and procedural rights.

Chapter X: Codes of Conduct and Guidelines

[Article 95: Codes of Conduct]: Encourages voluntary application of high-risk requirements to other AI systems.
[Article 96: Guidelines from the Commission]: Commission issues implementation guidelines with attention to SMEs and local authorities.

Chapter XI: Delegation of Power and Committee Procedure

[Articles 97-98]: Specify conditions for delegated acts and committee procedures.

Chapter XII: Penalties

[Article 99: Penalties]: Member States set effective, proportionate penalties; fines up to €35 million or 7% turnover for prohibited practices violations.
[Article 100: Administrative Fines on Union Institutions]: Fines for non-compliant EU bodies.
[Article 101: Fines for GPAI Providers]: Commission can fine GPAI providers up to 3% turnover or €15 million.

Chapter XIII: Final Provisions

[Articles 102-110]: Amend existing EU regulations/directives for AI Act consistency.
[Article 111: AI Systems Already Placed on Market]: Transitional provisions with different compliance deadlines based on system nature.
[Article 112: Evaluation and Review]: Commission regularly evaluates need for Act amendments.
[Article 113: Entry into Force]: Regulation entered force August 2, 2024 with phased implementation.

EU AI Act Glossary: Complete Terms and Definitions

This comprehensive glossary defines essential terms from the

EU Artificial Intelligence Act (Regulation 2024/1689).
Understanding these definitions is crucial for compliance with the
AI Act’s requirements for providers, deployers, and other stakeholders.

Last updated: [Date] | Version: Official EU AI Act terminology

EU AI ACT Glossary

AAI Literacy

Skills, knowledge and understanding that allow providers, deployers and affected persons, taking into account their respective rights and obligations in the context of this Regulation, to make an informed deployment of AI systems, as well as to gain awareness about the opportunities and risks of AI and possible harm it can cause.

AI Office

The Commission’s function of contributing to the implementation, monitoring and supervision of AI systems and general-purpose AI models, and AI governance, provided for in Commission Decision of 24 January 2024; references in this Regulation to the AI Office shall be construed as references to the Commission.

AI Regulatory Sandbox

A controlled framework set up by a competent authority which offers providers or prospective providers of AI systems the possibility to develop, train, validate and test, where appropriate in real-world conditions, an innovative AI system, pursuant to a sandbox plan for a limited time under regulatory supervision.

AI System

A machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. Related: Recital 12

Authorised Representative

A natural or legal person located or established in the Union who has received and accepted a written mandate from a provider of an AI system or a general-purpose AI model to, respectively, perform and carry out on its behalf the obligations and procedures established by this Regulation.

B

Biometric Categorisation System

An AI system for the purpose of assigning natural persons to specific categories on the basis of their biometric data, unless it is ancillary to another commercial service and strictly necessary for objective technical reasons. Related: Recital 16

Biometric Data

Personal data resulting from specific technical processing relating to the physical, physiological or behavioral characteristics of a natural person, such as facial images or dactyloscopic data. Related: Recital 14

Biometric Identification

The automated recognition of physical, physiological, behavioral, or psychological human features for the purpose of establishing the identity of a natural person by comparing biometric data of that individual to biometric data of individuals stored in a database. Related: Recital 15

Biometric Verification

The automated, one-to-one verification, including authentication, of the identity of natural persons by comparing their biometric data to previously provided biometric data. Related: Recital 15

C

CE Marking

A marking by which a provider indicates that an AI system is in conformity with the requirements set out in Chapter III, Section 2 and other applicable Union harmonisation legislation providing for its affixing.

Common Specification

A set of technical specifications as defined in Article 2, point (4) of Regulation (EU) No 1025/2012, providing means to comply with certain requirements established under this Regulation.

Conformity Assessment

The process of demonstrating whether the requirements set out in Chapter III, Section 2 relating to a high-risk AI system have been fulfilled.

Conformity Assessment Body

A body that performs third-party conformity assessment activities, including testing, certification and inspection.

Critical Infrastructure

Critical infrastructure as defined in Article 2, point (4), of Directive (EU) 2022/2557.

D

Deep Fake

AI-generated or manipulated image, audio or video content that resembles existing persons, objects, places, entities or events and would falsely appear to a person to be authentic or truthful.

Deployer

A natural or legal person, public authority, agency or other body using an AI system under its authority except where the AI system is used in the course of a personal non-professional activity. Related: Recital 13

Distributor

A natural or legal person in the supply chain, other than the provider or the importer, that makes an AI system available on the Union market.

Downstream Provider

A provider of an AI system, including a general-purpose AI system, which integrates an AI model, regardless of whether the AI model is provided by themselves and vertically integrated or provided by another entity based on contractual relations.

E

Emotion Recognition System

An AI system for the purpose of identifying or inferring emotions or intentions of natural persons on the basis of their biometric data. Related: Recital 18

F

Floating-Point Operation

Any mathematical operation or assignment involving floating-point numbers, which are a subset of the real numbers typically represented on computers by an integer of fixed precision scaled by an integer exponent of a fixed base. Related: Recital 110

G

General-Purpose AI Model

An AI model, including where such an AI model is trained with a large amount of data using self-supervision at scale, that displays significant generality and is capable of competently performing a wide range of distinct tasks regardless of the way the model is placed on the market and that can be integrated into a variety of downstream systems or applications, except AI models that are used for research, development or prototyping activities before they are placed on the market. Related: Recitals 97, 98, and 99

General-Purpose AI System

An AI system which is based on a general-purpose AI model and which has the capability to serve a variety of purposes, both for direct use as well as for integration in other AI systems. Related: Recital 100

H

Harmonized Standard

A harmonized standard as defined in Article 2(1), point (c), of Regulation (EU) No 1025/2012.

High-Impact Capabilities

Capabilities that match or exceed the capabilities recorded in the most advanced general-purpose AI models. Related: Recital 110

I

Importer

A natural or legal person located or established in the Union that places on the market an AI system that bears the name or trademark of a natural or legal person established in a third country.

Informed Consent

A subject’s freely given, specific, unambiguous and voluntary expression of his or her willingness to participate in a particular testing in real-world conditions, after having been informed of all aspects of the testing that are relevant to the subject’s decision to participate.

Input Data

Data provided to or directly acquired by an AI system on the basis of which the system produces an output.

Instructions for Use

The information provided by the provider to inform the deployer of, in particular, an AI system’s intended purpose and proper use.

Intended Purpose

The use for which an AI system is intended by the provider, including the specific context and conditions of use, as specified in the information supplied by the provider in the instructions for use, promotional or sales materials and statements, as well as in the technical documentation.

L

Law Enforcement

Activities carried out by law enforcement authorities or on their behalf for the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including safeguarding against and preventing threats to public security.

Law Enforcement Authority

Either:

(a) any public authority competent for the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security; or
(b) any other body or entity entrusted by Member State law to exercise public authority and public powers for the purposes of the prevention, investigation, detection or prosecution of criminal offences or the execution of criminal penalties, including the safeguarding against and the prevention of threats to public security.

M

Making Available on the Market

The supply of an AI system or a general-purpose AI model for distribution or use on the Union market in the course of a commercial activity, whether in return for payment or free of charge.

Market Surveillance Authority

The national authority carrying out the activities and taking the measures pursuant to Regulation (EU) 2019/1020.

N

National Competent Authority

A notifying authority or a market surveillance authority; as regards AI systems put into service or used by Union institutions, agencies, offices and bodies, references to national competent authorities or market surveillance authorities in this Regulation shall be construed as references to the European Data Protection Supervisor.

Non-Personal Data

Data other than personal data as defined in Article 4, point (1), of Regulation (EU) 2016/679.

Notified Body

A conformity assessment body notified in accordance with this Regulation and other relevant Union harmonization legislation.

Notifying Authority

The national authority responsible for setting up and carrying out the necessary procedures for the assessment, designation and notification of conformity assessment bodies and for their monitoring.

O

Operator

A provider, product manufacturer, deployer, authorised representative, importer or distributor.

P

Performance of an AI System

The ability of an AI system to achieve its intended purpose.

Personal Data

Personal data as defined in Article 4, point (1), of Regulation (EU) 2016/679.

Placing on the Market

The first making available of an AI system or a general-purpose AI model on the Union market.

Post Remote Biometric Identification System

A remote biometric identification system other than a real-time remote biometric identification system. Related: Recital 17

Post-Market Monitoring System

All activities carried out by providers of AI systems to collect and review experience gained from the use of AI systems they place on the market or put into service for the purpose of identifying any need to immediately apply any necessary corrective or preventive actions.

Profiling

Profiling as defined in Article 4, point (4), of Regulation (EU) 2016/679.

Provider

A natural or legal person, public authority, agency or other body that develops an AI system or a general-purpose AI model or that has an AI system or a general-purpose AI model developed and places it on the market or puts the AI system into service under its own name or trademark, whether for payment or free of charge.

Publicly Accessible Space

Any publicly or privately owned physical place accessible to an undetermined number of natural persons, regardless of whether certain conditions for access may apply, and regardless of the potential capacity restrictions. Related: Recital 19

Putting into Service

The supply of an AI system for first use directly to the deployer or for own use in the Union for its intended purpose.

R

Real-Time Remote Biometric Identification System

A remote biometric identification system, whereby the capturing of biometric data, the comparison and the identification all occur without a significant delay, comprising not only instant identification, but also limited short delays in order to avoid circumvention. Related: Recital 17

Real-World Testing Plan

A document that describes the objectives, methodology, geographical, population and temporal scope, monitoring, organisation and conduct of testing in real-world conditions.

Reasonably Foreseeable Misuse

The use of an AI system in a way that is not in accordance with its intended purpose, but which may result from reasonably foreseeable human behaviour or interaction with other systems, including other AI systems.

Recall of an AI System

Any measure aiming to achieve the return to the provider or taking out of service or disabling the use of an AI system made available to deployers.

Remote Biometric Identification System

An AI system for the purpose of identifying natural persons, without their active involvement, typically at a distance through the comparison of a person’s biometric data with the biometric data contained in a reference database. Related: Recital 17

Risk

The combination of the probability of an occurrence of harm and the severity of that harm.

S

Safety Component

A component of a product or of an AI system which fulfils a safety function for that product or AI system, or the failure or malfunctioning of which endangers the health and safety of persons or property.

Sandbox Plan

A document agreed between the participating provider and the competent authority describing the objectives, conditions, timeframe, methodology and requirements for the activities carried out within the sandbox.

Sensitive Operational Data

Operational data related to activities of prevention, detection, investigation or prosecution of criminal offences, the disclosure of which could jeopardise the integrity of criminal proceedings.

Serious Incident

An incident or malfunctioning of an AI system that directly or indirectly leads to any of the following:

(a) the death of a person, or serious harm to a person’s health;
(b) a serious and irreversible disruption of the management or operation of critical infrastructure;
(c) the infringement of obligations under Union law intended to protect fundamental rights;
(d) serious harm to property or the environment.

Special Categories of Personal Data

The categories of personal data referred to in Article 9(1) of Regulation (EU) 2016/679, Article 10 of Directive (EU) 2016/680 and Article 10(1) of Regulation (EU) 2018/1725.

Subject

For the purpose of real-world testing, means a natural person who participates in testing in real-world conditions.

Substantial Modification

A change to an AI system after its placing on the market or putting into service which is not foreseen or planned in the initial conformity assessment carried out by the provider and as a result of which the compliance of the AI system with the requirements set out in Chapter III, Section 2 is affected or results in a modification to the intended purpose for which the AI system has been assessed. Related: Recital 128

Systemic Risk

A risk that is specific to the high-impact capabilities of general-purpose AI models, having a significant impact on the Union market due to their reach, or due to actual or reasonably foreseeable negative effects on public health, safety, public security, fundamental rights, or the society as a whole, that can be propagated at scale across the value chain. Related: Recital 110

T

Testing Data

Data used for providing an independent evaluation of the AI system in order to confirm the expected performance of that system before its placing on the market or putting into service.

Testing in Real-World Conditions

The temporary testing of an AI system for its intended purpose in real-world conditions outside a laboratory or otherwise simulated environment, with a view to gathering reliable and robust data and to assessing and verifying the conformity of the AI system with the requirements of this Regulation and it does not qualify as placing the AI system on the market or putting it into service within the meaning of this Regulation, provided that all the conditions laid down in Article 57 or 60 are fulfilled.

Training Data

Data used for training an AI system through fitting its learnable parameters.

V

Validation Data

Data used for providing an evaluation of the trained AI system and for tuning its non-learnable parameters and its learning process in order, inter alia, to prevent underfitting or overfitting.

Validation Data Set

A separate data set or part of the training data set, either as a fixed or variable split.

W

Widespread Infringement

Any act or omission contrary to Union law protecting the interest of individuals, which:

(a) has harmed or is likely to harm the collective interests of individuals residing in at least two Member States other than the Member State in which:
- (i) the act or omission originated or took place;
- (ii) the provider concerned, or, where applicable, its authorised representative is located or established; or
- (iii) the deployer is established, when the infringement is committed by the deployer;
(b) has caused, causes or is likely to cause harm to the collective interests of individuals and has common features, including the same unlawful practice or the same interest being infringed, and is occurring concurrently, committed by the same operator, in at least three Member States.

Withdrawal of an AI System

Any measure aiming to prevent an AI system in the supply chain being made available on the market.

EU AI Act Fine Structure

Maximum Penalties by Violation Type

Prohibited AI (Most Serious)

Violation: Using banned AI systems (Article 5)

Companies: €35 million OR 7% of global annual revenue (whichever is higher)
EU Institutions: €1.5 million

Other Violations

Violations: Breaking rules for providers, importers, distributors, deployers, transparency

Companies: €15 million OR 3% of global annual revenue (whichever is higher)
EU Institutions: €750,000

False Information

Violation: Lying to authorities or providing misleading information

Companies: €7.5 million OR 1% of global annual revenue (whichever is higher)

Special Categories

Small Businesses (SMEs)

Pay the lower of percentage OR fixed amount
Ensures fines don’t destroy small companies
Applies to all violation types

General-Purpose AI Providers

Maximum: €15 million OR 3% of global revenue
Enforced by: European Commission directly
Violations include:
- Breaking GPAI rules
- Refusing to provide information
- Blocking model evaluation
- Ignoring compliance orders

How Fines Are Calculated

Authorities consider these factors:

Severity Factors:

Nature and gravity of violation
How long it lasted
Number of people affected
Damage caused
Intent (on purpose vs. accident)

Company Factors:

Size and market share
Annual revenue
Previous violations
Financial benefit gained

Cooperation Factors:

Self-reporting the violation
Helping with investigation
Actions to fix the problem
Measures to prevent repeat

Enforcement Process

Detection
- Market surveillance finds violation
- Someone files complaint
- Company self-reports
Investigation
- Authorities gather evidence
- Company can respond
- All circumstances reviewed
Decision
- Fine amount calculated
- Company notified
- Appeal rights explained
Payment
- Company fines → National budget
- EU institution fines → EU budget
- Annual reporting to Commission

Quick Reference Table

Violation	Company Fine	EU Institution Fine
Banned AI	€35M or 7%	€1.5M
Other violations	€15M or 3%	€750K
False info	€7.5M or 1%	N/A
GPAI violations	€15M or 3%	N/A

For companies: Always the HIGHER of fixed amount or percentage

Key Points

Double punishment avoided – Can’t be fined twice for same violation
Appeal rights – All fines can be challenged in court
Proportionality – Fines match the severity and company size
Annual reporting – All fines tracked and reported to EU Commission

EU AI ACT Key Dates & Timeline

Before 2002:

Prior to 2002/58/EC: Existing Union law protects private life and communications, providing conditions for data storage and access from terminal equipment (Recital 10).

2002:

July 12, 2002: Directive 2002/58/EC concerning the processing of personal data and the protection of privacy in the electronic communications sector is adopted (Recital 10).
June 13, 2002: Council Framework Decision 2002/584/JHA on the European arrest warrant and surrender procedures between Member States is adopted, serving as a basis for criminal offences listed in Annex II of the AI Act (Recital 33).

2003:

May 6, 2003: Commission Recommendation 2003/361/EC concerning the definition of micro, small and medium-sized enterprises is adopted (Recital 143, 146).

2005:

May 11, 2005: Directive 2005/29/EC concerning unfair business-to-consumer commercial practices is adopted, with its prohibitions being complementary to those in the AI Act (Recital 29).

2006:

May 17, 2006: Directive 2006/42/EC on machinery is adopted (Recital 46, Annex I.A.1).

2008:

July 9, 2008: Regulation (EC) No 765/2008 setting out requirements for accreditation and market surveillance is adopted (Recital 9, 28).
July 9, 2008: Decision No 768/2008/EC on a common framework for the marketing of products is adopted (Recital 9, 126).
March 11, 2008: Regulation (EC) No 300/2008 on common rules in the field of civil aviation security is adopted (Recital 49, Annex I.B.13).
April 23, 2008: Directive 2008/48/EC on credit agreements for consumers is adopted (Recital 158).

2009:

June 18, 2009: Directive 2009/48/EC on the safety of toys is adopted (Annex I.A.2).
July 13, 2009: Regulation (EC) No 810/2009 establishing a Community Code on Visas is adopted (Recital 60).
November 25, 2009: Directive 2009/138/EC on the taking-up and pursuit of the business of Insurance and Reinsurance (Solvency II) is adopted (Recital 158).

2012:

October 25, 2012: Regulation (EU) No 1025/2012 on European standardisation is adopted (Recital 121, 40, 41).

2013:

February 5, 2013: Regulation (EU) No 167/2013 on the approval and market surveillance of agricultural and forestry vehicles is adopted (Recital 49, Annex I.B.15).
January 15, 2013: Regulation (EU) No 168/2013 on the approval and market surveillance of two- or three-wheel vehicles and quadricycles is adopted (Recital 49, Annex I.B.14).
June 26, 2013: Regulation (EU) No 575/2013 on prudential requirements for credit institutions is adopted (Recital 158).
June 26, 2013: Directive 2013/32/EU on common procedures for granting and withdrawing international protection is adopted (Recital 60).
June 26, 2013: Directive 2013/36/EU on access to the activity of credit institutions is adopted (Recital 158).

2014:

July 23, 2014: Directive 2014/90/EU on marine equipment is adopted (Recital 49, Annex I.B.16).
February 4, 2014: Directive 2014/17/EU on credit agreements for consumers relating to residential immovable property is adopted (Recital 158).
February 26, 2014: Directive 2014/31/EU on the harmonisation of laws relating to non-automatic weighing instruments is adopted (Recital 74).
February 26, 2014: Directive 2014/32/EU on the harmonisation of laws relating to measuring instruments is adopted (Recital 74).
February 26, 2014: Directive 2014/33/EU on lifts and safety components for lifts is adopted (Annex I.A.4).
February 26, 2014: Directive 2014/34/EU on equipment and protective systems intended for use in potentially explosive atmospheres is adopted (Annex I.A.5).
April 16, 2014: Directive 2014/53/EU on the harmonisation of laws relating to radio equipment is adopted (Annex I.A.6).
May 15, 2014: Directive 2014/68/EU on pressure equipment is adopted (Annex I.A.7).

2016:

April 27, 2016: Regulation (EU) 2016/679 (General Data Protection Regulation – GDPR) is adopted (Recital 10, 14, 70, 94).
April 27, 2016: Directive (EU) 2016/680 on the protection of natural persons with regard to the processing of personal data by competent authorities for law enforcement purposes is adopted (Recital 10, 14, 38, 94).
March 9, 2016: Regulation (EU) 2016/424 on cableway installations is adopted (Annex I.A.8).
March 9, 2016: Regulation (EU) 2016/425 on personal protective equipment is adopted (Annex I.A.9).
March 9, 2016: Regulation (EU) 2016/426 on appliances burning gaseous fuels is adopted (Annex I.A.10).
January 20, 2016: Directive (EU) 2016/97 on insurance distribution is adopted (Recital 158).
May 11, 2016: Directive (EU) 2016/797 on the interoperability of the rail system within the European Union is adopted (Recital 49, Annex I.B.17).
October 26, 2016: Directive (EU) 2016/2102 on the accessibility of websites and mobile applications of public sector bodies is adopted (Recital 80).

2017:

April 5, 2017: Regulation (EU) 2017/745 on medical devices is adopted (Recital 46, 51, 84, 147, Annex I.A.11).
April 5, 2017: Regulation (EU) 2017/746 on in vitro diagnostic medical devices is adopted (Recital 46, 51, 147, Annex I.A.12).
November 30, 2017: Regulation (EU) 2017/2226 establishing an Entry/Exit System (EES) is adopted (Annex X.4).

2018:

May 30, 2018: Regulation (EU) 2018/858 on the approval and market surveillance of motor vehicles and their trailers is adopted (Recital 49, Annex I.B.18).
July 4, 2018: Regulation (EU) 2018/1139 on common rules in the field of civil aviation and establishing a European Union Aviation Safety Agency is adopted (Recital 49, Annex I.B.20).
October 23, 2018: Regulation (EU) 2018/1725 on the protection of natural persons with regard to the processing of personal data by the Union institutions, bodies, offices and agencies is adopted (Recital 10, 14, 70).
September 12, 2018: Regulation (EU) 2018/1240 establishing a European Travel Information and Authorisation System (ETIAS) is adopted (Annex X.5.a).
September 12, 2018: Regulation (EU) 2018/1241 amending Regulation (EU) 2016/794 for ETIAS is adopted (Annex X.5.b).
November 28, 2018: Regulation (EU) 2018/1860 on the use of SIS for return of illegally staying third-country nationals is adopted (Annex X.1.a).
November 28, 2018: Regulation (EU) 2018/1861 on the establishment, operation and use of SIS in border checks is adopted (Annex X.1.b).
November 28, 2018: Regulation (EU) 2018/1862 on the establishment, operation and use of SIS in police and judicial cooperation is adopted (Annex X.1.c).

2019:

June 20, 2019: Regulation (EU) 2019/1020 on market surveillance and compliance of products is adopted (Recital 9, 149, 156, 158, 161, 164, 166, 170, 74, 75, 79, 84).
November 27, 2019: Regulation (EU) 2019/2144 on type-approval requirements for motor vehicles and their trailers is adopted (Recital 49, Annex I.B.19).
April 17, 2019: Regulation (EU) 2019/881 on ENISA (the European Union Agency for Cybersecurity) and on information and communications technology cybersecurity certification (Cybersecurity Act) is adopted (Recital 78, 122).
April 17, 2019: Directive (EU) 2019/790 on copyright and related rights in the Digital Single Market is adopted (Recital 104, 105, 106).
April 17, 2019: Regulation (EU) 2019/816 establishing a centralised system for the identification of Member States holding conviction information on third-country nationals and stateless persons (ECRIS-TCN) is adopted (Annex X.6).
May 20, 2019: Regulation (EU) 2019/817 establishing a framework for interoperability between EU information systems in the field of borders and visa is adopted (Annex X.7.a).
May 20, 2019: Regulation (EU) 2019/818 establishing a framework for interoperability between EU information systems in the field of police and judicial cooperation, asylum and migration is adopted (Annex X.7.b).
October 23, 2019: Directive (EU) 2019/1937 on the protection of persons who report breaches of Union law (Whistleblower Directive) is adopted (Recital 172).
April 17, 2019: Directive (EU) 2019/882 on the accessibility requirements for products and services is adopted (Recital 29, 80, 131).

2020:

October 1, 2020: European Council Special meeting conclusions (EUCO 13/20) state the objective of promoting a human-centric approach to AI and being a global leader in secure, trustworthy, and ethical AI (Recital 8).
October 20, 2020: European Parliament resolution 2020/2012(INL) with recommendations to the Commission on a framework of ethical aspects of AI, robotics, and related technologies is adopted (Recital 8).
November 25, 2020: Directive (EU) 2020/1828 on representative actions for the protection of the collective interests of consumers is adopted (Annex I.B.20).

2021:

December 22, 2021: European Economic and Social Committee opinion on the AI Act (OJ C 517) is published (Recital 3).
July 7, 2021: Regulation (EU) 2021/1133 amending several regulations regarding the Visa Information System is adopted (Annex X.2.a).
July 7, 2021: Regulation (EU) 2021/1134 amending several regulations for the purpose of reforming the Visa Information System is adopted (Annex X.2.b).
2021: UNCRC General Comment No 25 on children’s rights in relation to the digital environment is developed (Recital 9, 48).

2022:

March 11, 2022: European Central Bank opinion on the AI Act (OJ C 115) is published (Recital 3).
February 28, 2022: Committee of the Regions opinion on the AI Act (OJ C 97) is published (Recital 3).
June 29, 2022: Commission notice ‘The “Blue Guide” on the implementation of EU product rules 2022’ is published (Recital 46, 64).
October 19, 2022: Regulation (EU) 2022/2065 on a Single Market For Digital Services (Digital Services Act) is adopted (Recital 11, 118, 120, 136).
May 30, 2022: Regulation (EU) 2022/868 on European data governance is adopted (Recital 141).
December 14, 2022: Directive (EU) 2022/2557 on the resilience of critical entities is adopted (Recital 33, 55).

2023:

May 10, 2023: Regulation (EU) 2023/988 on general product safety is adopted (Recital 166).
December 13, 2023: Regulation (EU) 2023/2854 on harmonised rules on fair access to and use of data (Data Act) is adopted (Recital 141).

2024:

January 24, 2024: Commission Decision C(2024) 390 establishing the European Artificial Intelligence Office (AI Office) is adopted (Recital 148, 64).
March 13, 2024: Position of the European Parliament on the AI Act (not yet published in the Official Journal) is established (Recital 3).
March 13, 2024: Regulation (EU) 2024/900 on the transparency and targeting of political advertising is adopted (Recital 62).
May 14, 2024: Regulation (EU) 2024/1358 on the establishment of ‘Eurodac’ for biometric data comparison is adopted (Annex X.3).
May 21, 2024: Decision of the Council on the AI Act is established (Recital 3).
June 13, 2024: REGULATION (EU) 2024/1689 of the European Parliament and of the Council (Artificial Intelligence Act) is adopted (Document Title).
July 12, 2024: The Artificial Intelligence Act is published in the Official Journal of the European Union (Publication Date).
August 1, 2024: The power to adopt delegated acts referred to in various articles is conferred on the Commission for a period of five years (Article 97(2)).
November 2, 2024: Member States must identify and make publicly available a list of national public authorities or bodies that supervise or enforce Union law protecting fundamental rights in relation to high-risk AI systems (Article 77(2)).

2025:

February 2, 2025: Chapters I (General Provisions) and II (Prohibited AI Practices) of the AI Act begin to apply (Article 113(a)).
May 2, 2025: Codes of practice for general-purpose AI models should be ready (Article 56(9)).
August 2, 2025: Chapter III Section 4 (Notifying Authorities and Notified Bodies), Chapter V (General-Purpose AI Models), Chapter VII (Governance), Chapter XII (Penalties), and Article 78 (Confidentiality) begin to apply, with the exception of Article 101 (Fines for providers of general-purpose AI models) (Article 113(b)).
August 2, 2025: Provisions on penalties begin to apply (Recital 179).
August 2, 2025: Member States must make publicly available information on how competent authorities and single points of contact can be contacted (Article 70(2)).
August 2, 2025: Member States must lay down and notify to the Commission the rules on penalties, including administrative fines (Recital 179).
August 2, 2025: Obligations for providers of general-purpose AI models begin to apply (Recital 179).
August 2, 2025: Commission guidance to facilitate compliance with serious incident reporting obligations is to be issued (Article 73(7)).

2026:

February 2, 2026: The Commission, after consulting the Board, is to provide guidelines specifying the practical implementation of Article 6 (classification of high-risk AI systems) with examples (Article 6(5)).
February 2, 2026: The Commission is to adopt an implementing act laying down detailed provisions and a template for the post-market monitoring plan (Article 72(3)).
August 2, 2026: Member States must ensure that their competent authorities establish at least one AI regulatory sandbox at national level, which must be operational (Article 57(1)).
August 2, 2026: The main body of the AI Act begins to apply (Article 113).

2027:

August 2, 2027: Providers of general-purpose AI models that were placed on the market before August 2, 2025, must comply with the obligations of the Regulation (Article 111(3)).

2028:

August 2, 2028 and every four years thereafter: The Commission is to evaluate and report to the European Parliament and Council on the need for amendments to Annex III (high-risk areas), Article 50 (transparency measures), and the effectiveness of the supervision and governance system (Article 112(2)).
August 2, 2028 and every four years thereafter: The Commission is to report on the review of progress on the energy-efficient development of general-purpose AI models (Article 112(6)).
August 2, 2028 and every three years thereafter: The Commission is to evaluate the impact and effectiveness of voluntary codes of conduct for non-high-risk AI systems (Article 112(7)).
August 2, 2028: The Commission is to evaluate the functioning of the AI Office and report to the European Parliament and Council (Article 112(5)).

2029:

August 2, 2029 and every four years thereafter: The Commission is to submit a report on the evaluation and review of the entire Regulation to the European Parliament and Council, potentially including proposals for amendment (Article 112(3)).

2030:

August 2, 2030: Providers and deployers of high-risk AI systems intended to be used by public authorities must comply with the requirements and obligations of the Regulation (Article 111(2)).
December 31, 2030: AI systems that are components of large-scale IT systems listed in Annex X, placed on the market or put into service before August 2, 2027, must be brought into compliance (Article 111(1)).

2031:

August 2, 2031: The Commission is to carry out an assessment of the enforcement of the Regulation and report to the European Parliament, the Council, and the European Economic and Social Committee (Article 112(13)).

Ongoing:

Annually (until end of delegation of power): The Commission assesses the need for amendment of Annex III and the list of prohibited AI practices (Article 112(1)).
Regularly: National market surveillance authorities and data protection authorities submit annual reports to the Commission on the use of ‘real-time’ remote biometric identification systems (Article 5(6)).
Regularly: The Commission publishes annual reports on the use of real-time remote biometric identification systems based on aggregated data (Article 5(7)).
As needed: The Commission can adopt delegated acts to amend conditions for high-risk AI systems, lists of high-risk AI systems, technical documentation, EU declaration of conformity, conformity assessment procedures, thresholds for general-purpose AI models with systemic risk, and transparency information for general-purpose AI models (Article 97).
As needed: The AI Office (Commission) can take actions to monitor and enforce compliance by providers of general-purpose AI models (Article 88, 89).
As needed: The scientific panel may provide qualified alerts to the AI Office regarding general-purpose AI models (Article 90).
As needed: Member States report to the Commission on the status of financial and human resources of national competent authorities every two years (Article 70(6)).

EU AI ACT Risk Assessment

EU AI Act Risk Assessment Checklist & Template

Document Version: 1.0
Based on: EU AI Act (Regulation (EU) 2024/1689)
Last Updated: [Date]

Implementation Timeline & Stage Gates

Stage	When to Perform	Key Deliverables
Stage 1: Conception	During initial AI system design	Initial Classification Report
Stage 2: Development	Throughout development phase	Risk Management Documentation, Data Governance Plan
Stage 3: Pre-Market	Before market placement	Technical Documentation, Conformity Assessment, CE Marking
Stage 4: Pre-Deployment	Before operational use	FRIA (if applicable), User Instructions
Stage 5: Post-Market	Continuous monitoring	Incident Reports, Monitoring Logs

Section 1: Initial Classification Assessment

Stage: Conception
Deliverable: Classification Determination Report

1.1 System Identification

Field	Information Required	Response
AI System Name	Official designation	_________
Version	Current version number	_________
Provider Name	Legal entity name	_________
Provider Registration	Company registration number	_________
Intended Purpose	Clear description of primary use	_________
Target Users	Who will deploy/use the system	_________

1.2 High-Risk Classification Screening

[Reference: Article 6]

Safety Component Check

Does your AI system fall under any of these categories?

Machinery (Annex I)
Toys
Lifts
Medical Devices
In Vitro Diagnostic Medical Devices
Radio Equipment
Pressure Equipment
Recreational Craft/Personal Watercraft
Cableway Installations
Gas Appliances
Civil Aviation Systems
Two/Three-Wheel Vehicles
Agricultural/Forestry Vehicles
Marine Equipment
Rail System Components
Motor Vehicles
None of the above

Requires third-party conformity assessment? [ ] Yes [ ] No

Annex III Category Check

[Reference: Annex III]

Check all that apply:

1. Biometric Systems

Remote biometric identification (real-time or post)
Biometric categorization based on sensitive attributes
Emotion recognition systems

2. Critical Infrastructure

Safety components for road traffic management
Safety components for water/gas/heating/electricity supply
Safety components for critical digital infrastructure

3. Education and Vocational Training

Determining access/admission to educational institutions
Assigning persons to educational institutions
Evaluating learning outcomes/student assessment
Monitoring prohibited behavior during tests

4. Employment and Worker Management

Recruitment or selection (advertising, screening, evaluating)
Decisions affecting work relationships (promotion, termination)
Task allocation based on behavior/personal traits
Monitoring and evaluating performance/behavior

5. Essential Services and Benefits

Eligibility assessment for public assistance benefits
Creditworthiness evaluation/credit scoring
Risk assessment/pricing for life/health insurance
Emergency services dispatch systems

6. Law Enforcement

Individual risk assessment
Polygraph or similar detection systems
Evidence reliability evaluation
Recidivism risk assessment
Profiling for crime detection/prevention/investigation

7. Migration, Asylum and Border Control

Polygraph-type systems
Risk assessment for security/health/migration risks
Examination of asylum/visa/residence applications
Detection/recognition/identification of persons

8. Administration of Justice

Assisting judicial authorities in research/interpretation
Influencing election/referendum outcomes

1.3 High-Risk Derogation Assessment

[Reference: Article 6(3)]

Answer these questions to determine if derogation applies:

Does the AI system perform ONLY narrow procedural tasks?
- Yes (describe): _____________
- No
Does it ONLY improve results of previously completed human activity?
- Yes (describe): _____________
- No
Does it ONLY detect patterns/deviations without influencing human assessment?
- Yes (describe): _____________
- No
Is it ONLY preparatory to human assessment?
- Yes (describe): _____________
- No
⚠️ CRITICAL: Does the system perform profiling of natural persons?
- Yes → ALWAYS HIGH-RISK
- No

Derogation Documentation Required: If claiming derogation, prepare detailed justification document

Classification Result:

High-Risk AI System → Continue with full checklist
Not High-Risk → Complete derogation documentation and register in EU database
Requires Further Assessment

Section 2: Risk Management System

Stage: Development
Deliverable: Risk Management Plan & Risk Register
[Reference: Article 9]

2.1 Risk Identification Matrix

Risk Category	Identified Risks	Probability (1-5)	Impact (1-5)	Risk Score
Health Risks
Description:	_____________	___	___	___
Safety Risks
Description:	_____________	___	___	___
Fundamental Rights
Description:	_____________	___	___	___
Reasonably Foreseeable Misuse
Description:	_____________	___	___	___

2.2 Vulnerable Groups Impact Assessment

Persons under 18:

No interaction/impact
Indirect impact possible
Direct interaction/impact → Describe measures: _____________

Other vulnerable groups (elderly, persons with disabilities, etc.):

Identified groups: _____________
Specific risks: _____________
Mitigation measures: _____________

2.3 Risk Mitigation Measures

For each identified risk, complete:

Risk ID	Mitigation Strategy	Implementation Method	Residual Risk Level	Acceptable?
R001				[ ] Yes [ ] No
R002				[ ] Yes [ ] No

2.4 Testing Plan

[Reference: Article 9(6-8)]

Pre-defined Metrics:

Accuracy threshold: _____%
Robustness criteria: _____________
Safety performance indicators: _____________

Testing Schedule:

Unit testing completed
Integration testing completed
System testing completed
Real-world testing planned (if applicable)

Real-World Testing Requirements (if applicable):

Testing location: _____________
Duration: _____________
Oversight measures: _____________
Ethics approval obtained: [ ] Yes [ ] No [ ] N/A

Section 3: Data Governance Assessment

Stage: Development
Deliverable: Data Governance Documentation
[Reference: Article 10]

3.1 Data Quality Framework

Data Aspect	Documentation Required	Status
Collection Process	Source, method, date	[ ] Complete
Data Origin	Original purpose, consent basis	[ ] Complete
Preparation Operations	Annotation, labeling, cleaning steps	[ ] Complete
Key Assumptions	What data measures/represents	[ ] Complete
Volume Assessment	Quantity and suitability analysis	[ ] Complete

3.2 Bias Detection and Mitigation

Bias Assessment Checklist:

Gender bias analysis completed
Racial/ethnic bias analysis completed
Age bias analysis completed
Disability bias analysis completed
Socioeconomic bias analysis completed
Geographic bias analysis completed

Identified Biases:

Type: _________ | Mitigation: _________
Type: _________ | Mitigation: _________

3.3 Data Gaps and Shortcomings

Gap Identified	Impact on Compliance	Remediation Action	Timeline

Special Category Data Processing (if applicable):

Strictly necessary for bias detection/correction
Appropriate safeguards implemented
Limited to minimum necessary
Documented justification prepared

Section 4: Human Oversight Design

Stage: Development
Deliverable: Human Oversight Specification
[Reference: Article 14]

4.1 Oversight Capabilities Checklist

System Understanding:

Clear documentation of capabilities provided
Limitations explicitly stated
Training materials prepared

Human Control Measures:

Output interpretation tools provided
Override functionality implemented
System interruption mechanism available
Disregard output option clearly marked

4.2 Enhanced Requirements for Biometric Systems

Two-Person Verification (if applicable):

Applies to our system
Verification protocol established
Competence requirements defined
Exception justification prepared (if claiming disproportionality)

Section 5: Fundamental Rights Impact Assessment (FRIA)

Stage: Pre-Deployment
Deliverable: FRIA Report
[Reference: Article 27]

5.1 FRIA Applicability

Required if you are:

Body governed by public law
Private entity providing public services
Deploying AI for creditworthiness/credit scoring
Deploying AI for life/health insurance risk assessment

5.2 FRIA Components

Component	Description	Documented?
Deployment Process	Where/how AI will be used	[ ] Yes
Usage Period	Duration and frequency	[ ] Yes
Affected Persons	Categories and estimated numbers	[ ] Yes
Specific Risks	To fundamental rights	[ ] Yes
Oversight Measures	Human supervision details	[ ] Yes
Mitigation Plan	If risks materialize	[ ] Yes
Complaints Mechanism	Internal governance	[ ] Yes

Market Surveillance Authority Notified: [ ] Yes [ ] No [ ] Pending

Section 6: Technical Compliance Requirements

Stage: Pre-Market
Deliverable: Technical Documentation Package

6.1 Performance Standards

[Reference: Article 15]

Requirement	Target Metric	Achieved	Evidence
Accuracy	___%	[ ] Yes [ ] No	_______
Robustness	[Define]	[ ] Yes [ ] No	_______
Cybersecurity	[Standards]	[ ] Yes [ ] No	_______

6.2 Transparency Obligations

[Reference: Article 13 & Article 50]

High-Risk System Requirements:

Instructions for use prepared
Intended purpose clearly stated
Performance specifications documented
Limitations disclosed
Expected lifetime specified
Maintenance requirements defined

Additional Transparency Requirements (if applicable):

AI interaction disclosure implemented
Synthetic content marking enabled
Emotion recognition/biometric categorization disclosure ready
Deepfake disclosure mechanism in place

6.3 Logging and Traceability

[Reference: Article 12]

Automatic Logging Implemented:

Event recording capability confirmed
Log retention period defined: _____ months/years
Access controls established
Log format documented

Section 7: Documentation Package

Stage: Pre-Market
Deliverable: Complete Documentation Set

7.1 Technical Documentation Checklist

[Reference: Article 11 & Annex IV]

General AI system description
Detailed development process documentation
Data requirements specification
Training methodology documentation
Validation and testing reports
Risk management system documentation
Post-market monitoring plan
Cybersecurity measures description
Performance metrics and limitations
Change management procedures

7.2 Quality Management System

[Reference: Article 17]

QMS Components Documented:

Regulatory compliance strategy
Design control procedures
Development and quality control procedures
Testing and validation procedures
Data management systems
Risk management integration
Post-market monitoring procedures
Incident reporting procedures
Communication procedures
Record-keeping systems
Resource management
Accountability framework

7.3 Conformity Documentation

[Reference: Articles 47-49]

EU Declaration of Conformity prepared
CE marking affixed (physical/digital)
EU database registration completed
Registration number obtained: _____________

Section 8: Post-Market Monitoring

Stage: Post-Market (Ongoing)
Deliverable: Monitoring Reports & Incident Logs

8.1 Monitoring System Setup

[Reference: Article 72]

Monitoring Plan Elements:

Performance metrics tracking system
User feedback collection mechanism
Incident detection procedures
Regular review schedule established
Analysis methodology documented

8.2 Serious Incident Reporting

[Reference: Article 73]

Incident Categories:

Death or serious damage to health
Serious damage to property (>€1 million)
Serious harm to environment
Breach causing harm to fundamental rights
Serious disruption of critical infrastructure

Reporting Timeline:

Immediately upon establishing causal link
Maximum 15 days after awareness
Death/widespread infringement: report immediately

Incident Log:

Date	Incident Type	Severity	Reported	Resolution
			[ ] Yes [ ] No

Section 9: General-Purpose AI Models (if applicable)

Stage: Development/Pre-Market
Deliverable: GPAI Documentation Package
[Reference: Articles 51-55]

9.1 Systemic Risk Assessment

Computational Power Check:

Training FLOPs: ____________
Exceeds 10^25 FLOPs? [ ] Yes [ ] No

Commission Designation Check:

Not designated
Under review
Designated as systemic risk

9.2 Additional Requirements for Systemic Risk

If systemic risk identified:

Model evaluation completed
Adversarial testing (red-teaming) performed
Systemic risk assessment documented
Incident reporting procedures enhanced
Cybersecurity measures upgraded

Section 10: Final Compliance Verification

Stage: Pre-Market/Pre-Deployment
Deliverable: Compliance Certificate

10.1 Pre-Market Checklist

Requirement	Status	Evidence Location
Risk classification completed	[ ] Done	_______
Risk management system operational	[ ] Done	_______
Technical documentation complete	[ ] Done	_______
Testing completed	[ ] Done	_______
QMS established	[ ] Done	_______
Conformity assessment done	[ ] Done	_______
CE marking affixed	[ ] Done	_______
EU database registration	[ ] Done	_______

10.2 Deployment Readiness

FRIA completed (if required)
User instructions finalized
Human oversight measures active
Transparency requirements met
Monitoring systems operational
Incident response team designated

10.3 Compliance Declaration

Declaration: I hereby confirm that all applicable requirements of the EU AI Act have been assessed and addressed for this AI system.

Responsible Person:

Name: _____________
Title: _____________
Date: _____________
Signature: _____________

Appendix: Key Deliverables Summary

Stage	Key Deliverables	Storage Location	Retention Period
Conception	Classification Report	_______	10 years
Development	Risk Management Plan	_______	10 years
Development	Data Governance Docs	_______	10 years
Pre-Market	Technical Documentation	_______	10 years
Pre-Market	QMS Documentation	_______	10 years
Pre-Market	Conformity Declaration	_______	10 years
Pre-Deployment	FRIA Report	_______	10 years
Post-Market	Monitoring Reports	_______	10 years
Post-Market	Incident Reports	_______	10 years

Important Notes:

Documentation Retention: All documentation must be kept for 10 years after the AI system is placed on market or put into service (Article 18)
Financial Institutions: May use existing governance frameworks for some requirements (Article 17(8))
Updates Required: This checklist must be updated when:
- AI system undergoes substantial modification
- New risks are identified
- Regulatory guidance changes
- Incidents occur requiring corrective action
Authority Cooperation: Be prepared to provide any documentation to competent authorities upon request
Legal Disclaimer: This checklist is a tool to assist with EU AI Act compliance. Organizations should seek legal counsel for specific compliance questions.

End of Checklist

For the most current version of the EU AI Act and related guidance, visit: EU AI Act Official Text

EU AI ACT Guides

Select the appropriate guide below (via the tabs) to see details about the EU AI ACT for your experience level.

EU AI Act: A Beginner’s Guide

Reading time: 15 minutes

What is the EU AI Act?

The EU AI Act is a new law that controls how artificial intelligence (AI) can be used in Europe. Think of it as a rulebook that makes sure AI is safe and fair for everyone. It’s the world’s first major law about AI, and it started on August 2, 2024.

Why Does This Law Exist?

The EU created this law for five main reasons:

Keep people safe – AI should help humans, not harm them
Protect your rights – Your privacy and freedom matter
Make rules clear – Companies need to know what’s allowed
Stop confusion – All EU countries follow the same rules
Help small businesses – Not just big tech companies can use AI

Think of it like traffic laws – we need rules so everyone stays safe and knows what to do.

Who Must Follow These Rules?

The law applies to different groups:

Providers

Companies that make AI systems
Like a toy manufacturer making a robot toy

Deployers

Organizations using AI in their work
Like a school using AI to grade tests

Importers

Businesses bringing AI from other countries into Europe
Like someone importing smartphones with AI features

Distributors

Stores or websites selling AI products
Like an electronics shop

You and Me

Regular people are affected when AI is used on us
But we don’t have to follow special rules

The Four Risk Levels (Like a Safety Scale)

The EU AI Act sorts AI into four groups, like a danger scale from safe to banned:

1. 🚫 BANNED AI (Unacceptable Risk)

These are completely forbidden

What’s banned:

Mind tricks – AI that secretly controls what you do
Social scores – Rating people like in a video game
Face scanning in public – Police can’t scan everyone’s face in crowds (with very few exceptions)
Emotion readers at work/school – Bosses and teachers can’t use AI to read your feelings
Unfair profiling – Judging if someone might commit crimes based on their personality

When banned: February 2, 2025

2. ⚠️ HIGH-RISK AI

These need lots of checks and rules

Examples:

AI that helps hire people for jobs
AI that grades students
AI that decides who gets a loan
AI used by police
AI in medical devices
AI controlling traffic lights

What they must do:

Pass safety tests
Have a “CE” mark (like a safety sticker)
Register in an EU database
Let humans override decisions
Keep records of what they do
Be transparent about how they work

3. ℹ️ LIMITED RISK AI

These just need to be honest

Examples:

Chatbots (must say they’re not human)
Deepfakes (must say they’re fake)
AI creating images or videos

Main rule: Tell people when they’re dealing with AI

4. ✅ MINIMAL RISK AI

Most AI falls here – no special rules

Examples:

Spam filters
Video game AI
Recommendation systems (like “you might also like…”)

Special Rules for Super-Smart AI (GPAI)

Some AI systems are really powerful and can do many things (like ChatGPT). These are called “General-Purpose AI” or GPAI.

All GPAI must:

Keep technical records
Respect copyright
Say what data they trained on
Help other companies understand them

Extra-powerful GPAI must also:

Test for dangers
Report serious problems fast
Have strong security
Check for risks to society

What Companies Must Do

For High-Risk AI:

Risk Management
- Find dangers
- Fix problems
- Keep checking
Good Data
- Use fair information
- Remove errors
- Represent everyone
Clear Instructions
- Easy-to-understand manual
- List of risks
- How to use safely
Human Control
- People can stop the AI
- People understand what AI is doing
- No blind trust in AI
Keep Records
- Save what AI does
- Store for 6+ months
- Help investigations

Your Rights as a Person Under the EU AI Act

The law gives you important protections when organizations use AI systems that affect you:

🔍 Right to Know (Transparency)

AI systems must identify themselves and their artificial nature:

Chatbots must say they’re AI, not human
Deepfakes and AI content must be clearly labeled
Emotion recognition systems must inform you they’re active
Information must be clear and accessible, including for people with disabilities

🗣️ Right to Complain (Remedy)

You can challenge unfair AI treatment:

File complaints with your national market surveillance authority
Existing rights for consumer and data protection still apply
Authorities must investigate your concerns as part of monitoring
Whistleblowers get special protection when reporting violations

👤 Right to Human Review

Real people must oversee important AI decisions:

Qualified humans can monitor and override AI systems
Clear explanations required for decisions affecting your rights
Critical systems need verification by two trained people
Stop mechanisms must exist to interrupt AI operations

🔐 Right to Privacy Protection

Your data stays protected when used by AI:

GDPR still applies with all current privacy rights
Banned practices include mass surveillance and exploiting vulnerabilities
Data minimization required – AI can only use necessary data
Special protections for sensitive information like health or biometric data

The Punishment System (Fines)

Breaking the rules costs money:

Worst violations (banned AI):

Up to €35 million
OR 7% of company’s yearly income

Other violations:

Up to €15 million
OR 3% of company’s yearly income

Lying to authorities:

Up to €7.5 million
OR 1% of company’s yearly income

Smaller companies pay less

Important Dates to Remember

August 2, 2024 – Law officially started
February 2, 2025 – Banned AI rules begin
May 2, 2025 – Industry should have guidelines ready
August 2, 2025 – Rules for super-smart AI begin
August 2, 2026 – Most other rules begin
August 2, 2027 – Rules for AI in products begin

Who’s In Charge?

EU Level:

AI Office – Main AI police for Europe
AI Board – Representatives from each country
Expert Panel – Scientists who give advice

Your Country:

Each country picks its own AI authorities
They check companies follow rules
They help with complaints

Innovation Support

The law isn’t just about stopping bad AI. It also helps good AI grow:

AI Sandboxes

Safe spaces to test new AI
Government supervision
Helps small companies
Must exist by August 2026

Real-World Testing

Can test AI in real situations
Need permission first
Must protect people’s data
Requires consent (usually)

Why This Matters to You

Even if you don’t work with AI:

You’ll interact with AI – It’s everywhere
Your rights are protected – The law watches out for you
AI will be more trustworthy – Bad AI is banned
You’ll know when it’s AI – No more tricks
Humans stay in control – People make final decisions

Simple Summary

The EU AI Act is like a safety manual for AI. It:

Bans dangerous AI
Controls risky AI
Makes AI be honest
Protects your rights
Helps good AI develop
Punishes rule-breakers

Most importantly: AI should help humans, not replace or harm them.

So important, I’ll say it again: AI should help humans, not replace or harm them.

EU AI Act: Intermediate Practitioner’s Guide

For professionals implementing and managing AI compliance within organizations

Implementation Framework

The EU AI Act requires a strategic, risk-based approach to compliance. This guide provides actionable strategies for practitioners responsible for AI governance within their organizations.

Core Compliance Strategy

The Act’s foundation is a risk-based approach that scales requirements based on potential harm. Your implementation should focus on:

1. Continuous Risk Management

Implement iterative risk assessment throughout AI system lifecycles

Document all risk identification, analysis, and mitigation decisions
Include expert input in risk evaluation processes
Address both intended use and foreseeable misuse scenarios

2. Integration with Existing Systems

Leverage current compliance frameworks (medical devices, machinery, etc.)
Combine AI Act requirements with existing conformity assessments
Minimize duplication by integrating documentation and testing processes
Use established quality management systems as foundation

3. Standards-Based Compliance

Follow harmonized standards for presumption of conformity
Utilize common specifications where standards don’t exist
Document adherence to recognized technical frameworks
Stay updated on new standards publications

Resource Allocation Guide

Essential Investment Areas

Technical Resources

AI system documentation tools
Automated logging and monitoring systems
Risk assessment software
Compliance tracking platforms

Human Resources

AI compliance officers
Technical documentation specialists
Risk assessment experts
Data governance teams

Training Programs

Organization-wide AI literacy
Role-specific compliance training
Ongoing regulatory updates
Incident response procedures

Cost Optimization Strategies

For SMEs and Startups:

Access priority regulatory sandbox programs
Apply for reduced conformity assessment fees
Implement simplified quality management systems (microenterprises)
Utilize EU funding programs (Digital Europe, Horizon Europe)

For All Organizations:

Share compliance costs through industry consortiums
Leverage open-source compliance tools
Participate in sector-specific working groups
Use standardized documentation templates

Compliance Process Roadmap

Phase 1: System Classification

Timeline: Immediate

Inventory all AI systems (see our article for guidance).
- Document purpose and functionality
- Identify data inputs and outputs
- Map user interactions
Classify risk levels
- Check against Annex I (product safety)
- Review Annex III (high-risk uses)
- Identify GPAI models
- Document minimal/limited risk systems
Prioritize compliance efforts
- Focus on prohibited practices first
- Address high-risk systems next
- Plan for transparency obligations

Phase 2: Documentation Development

Timeline: 3-6 months

Technical Documentation Requirements:

System architecture and design
Data processing operations
Risk assessment results
Testing and validation reports
Human oversight measures
Performance metrics

Operational Documentation:

Quality management procedures
Incident response plans
User instructions
Maintenance guidelines
Change management processes

Phase 3: System Implementation

Timeline: 6-12 months

Data Governance

Establish data quality standards
Implement bias detection mechanisms
Create data provenance tracking
Document special category data processing

Technical Safeguards

Enable automatic event logging
Implement human override capabilities
Establish system monitoring
Create audit trails

Conformity Assessment

Select appropriate procedure (internal vs. notified body)
Prepare assessment documentation
Schedule third-party reviews if required
Obtain CE marking

Phase 4: Ongoing Compliance

Timeline: Continuous

Post-Market Monitoring

Track system performance metrics
Collect user feedback
Monitor for incidents
Update risk assessments

Incident Management

Establish reporting procedures
Create escalation protocols
Document corrective actions
Report serious incidents immediately

Team Coordination Structure

Governance Model

(article: build your governance committee).

Executive Level

AI Governance Board
Risk Committee oversight
Budget allocation
Strategic compliance decisions

Management Level

Compliance Program Manager
Technical Lead
Legal/Regulatory Lead
Quality Assurance Lead

Operational Level

Documentation teams
Testing specialists
Monitoring analysts
Incident responders

Communication Protocols

Internal Coordination

Weekly compliance status meetings
Monthly risk review sessions
Quarterly board updates
Annual compliance assessments

External Engagement

Regular authority interactions
Industry working group participation
Notified body relationships
Stakeholder consultations

Quick Wins Checklist

Immediate Actions (By February 2025)

Audit for prohibited practices
- Emotion recognition in workplace/education
- Social scoring systems
- Manipulative AI techniques
- Biometric categorization systems
Establish governance structure
- Appoint AI compliance lead
- Form cross-functional team
- Define roles and responsibilities
- Create reporting lines
Begin documentation
- Start technical documentation templates
- Create data governance policies
- Draft user instructions
- Establish logging procedures

Short-term Priorities (3-6 months)

Complete system inventory
- Catalog all AI systems
- Classify risk levels
- Identify compliance gaps
- Prioritize remediation
Implement training programs
- Launch AI literacy initiatives
- Train compliance teams
- Educate system operators
- Brief executive leadership
Develop compliance infrastructure
- Select documentation tools
- Implement monitoring systems
- Create incident procedures
- Establish audit processes

Medium-term Goals (6-12 months)

Achieve full compliance
- Complete conformity assessments
- Obtain necessary certifications
- Register high-risk systems
- Implement all safeguards
Optimize processes
- Automate compliance workflows
- Integrate with existing systems
- Streamline documentation
- Enhance monitoring capabilities

Critical Deadlines

Date	Requirement	Action Needed
February 2, 2025	Prohibited practices ban	Cease all banned AI uses
May 2, 2025	GPAI codes of practice	Align with industry codes
August 2, 2025	GPAI model obligations	Implement model governance
August 2, 2025	Authorized representatives	Appoint EU representative
August 2, 2026	High-risk system compliance	Full compliance required
August 2, 2027	Product safety AI	Comply with Annex I requirements

Best Practices

Documentation Excellence

Use version control for all documents
Maintain clear audit trails
Create searchable archives
Implement regular reviews

Risk Management

Adopt ISO 31000 principles
Use quantitative risk metrics
Document mitigation measures
Update assessments regularly

Stakeholder Engagement

Inform workers about AI deployment
Consult with employee representatives
Engage with regulatory authorities
Participate in industry forums

Continuous Improvement

Monitor regulatory updates
Benchmark against peers
Implement lessons learned
Evolve compliance processes

Support Resources

Regulatory Sandboxes

Test innovative AI safely
Get regulatory guidance
Reduce compliance risks
Build authority relationships

Funding Opportunities

Digital Europe Programme
Horizon Europe grants
National innovation funds
SME-specific support

Industry Resources

Sector-specific guidelines
Compliance tool libraries
Best practice repositories
Expert networks

Next Steps

Assess your current state against these requirements
Build your compliance team with clear responsibilities
Create your implementation roadmap with realistic timelines
Begin documentation immediately for all AI systems
Engage with authorities early and proactively

Remember: Compliance is not a one-time project but an ongoing commitment to responsible AI governance. Start now, iterate often, and maintain continuous improvement.

Derrick Jackson

Founder: CISSP, CRISC, CCSP - Senior Director of Cloud Security Architecture & Risk

Note:

This is a living page and will continuously be updated & enhanced. Last updated: August 10th, 2025

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Contacts

AI Governance EU AI ACT Guide

EU AI Act Explained: Obligations, Risk Tiers & Who It Applies To

Table of Contents

Beginner

What is the EU AI Act

Intermediate

Implementation Roadmaps

Advanced

Compliance monitoring systems

EU AI ACT Article Tracker

EU AI ACT Risk Categories

Prohibited AI Systems Under the EU AI Act

High-Risk AI Systems Under the EU AI Act

General-Purpose AI (GPAI) Models Under the EU AI Act

WHAT THE EU AI ACT MEANS FOR YOU

EU AI ACT Essential Reference Tools

Click each card to learn more:

EU AI ACT QMS Requirements

EU AI Act - Article References

EU AI ACT Glossary

EU AI ACT Fines & Violations

EU AI ACT Timeline Events

EU AI ACT Risk Assessment

Role-Based Compliance

Documentaton & Tools Templates

Or expand text below:

Quality Management System (QMS) Requirements Under the EU AI Act

Purpose and Framework

Integration Options

Core QMS Requirements (Quality Management System Article 17)

1. Strategy for Regulatory Compliance

2. Management and Organization

3. Technical Standards and Specifications

4. Comprehensive Data Management

5. Documentation Requirements

6. Post-Market Monitoring

7. Authority Communication

Conformity Assessment and QMS

Notified Body Requirements

Alignment with International Standards

Implementation Timeline

Chapter I: General Provisions

Chapter II: Prohibited AI Practices

Chapter III: High-Risk AI Systems

Section 1: Classification

Section 2: Requirements

Section 3: Obligations

Section 4: Notifying Authorities and Notified Bodies

Section 5: Standards, Conformity Assessment, Certificates, Registration

Chapter IV: Transparency Obligations

Chapter V: General-Purpose AI Models

Section 1: Classification Rules

Section 2: Obligations for Providers of General-Purpose AI Models

Section 3: Obligations for GPAI Models with Systemic Risk

Section 4: Codes of Practice

Chapter VI: Measures in Support of Innovation

Chapter VII: Governance

Section 1: Governance at Union Level

Section 2: National Competent Authorities

Chapter VIII: EU Database

Chapter IX: Post-Market Monitoring, Information Sharing and Market Surveillance

Section 1: Post-Market Monitoring

Section 2: Sharing of Information

Section 3: Enforcement

Section 4: Remedies

Section 5: Supervision of General-Purpose AI Models

Chapter X: Codes of Conduct and Guidelines

Chapter XI: Delegation of Power and Committee Procedure

Chapter XII: Penalties

Chapter XIII: Final Provisions

This comprehensive glossary defines essential terms from the

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