Inside the EU AI Act: Your Classification Tool for Navigating High-Risk Compliance Requirements
The step-by-step framework every executive needs to turn regulatory ambiguity into actionable compliance strategy
Executive Summary
Most organizations cannot definitively answer a single, critical question: “Which of our AI systems trigger high-risk compliance requirements under the EU AI Act by August 2027?”
This ambiguity creates a dual financial trap. Misclassifying minimal-risk systems as high-risk forces organizations to incur unnecessary compliance costs—estimated at €6,000 to €7,000 in direct expenses per system - diverting essential resources toward mandatory high-risk infrastructure (risk management systems, technical documentation, governance frameworks) that the system doesn’t require. For organizations deploying dozens or hundreds of AI systems, this resource misallocation multiplies exponentially.
Underclassifying actual high-risk systems carries far more severe consequences. Organizations that fail to implement mandatory requirements such as data governance frameworks (Article 10) face penalties reaching €20 million or 4% of worldwide turnover per violation. If the underclassified system enables a prohibited AI practice, penalties escalate to €35 million or 7% of worldwide annual revenue. With a significant majority of organizations now using AI and many deploying multiple systems in production, the exposure from misclassification is existential.
With the August 2026 deadline for initial compliance and registration of high-risk systems quickly approaching, and the final enforcement of high-risk rules due by August 2027, the classification decision is no longer optional. It is your organization’s most consequential compliance decision.
This article provides the step-by-step classification framework that transforms regulatory ambiguity into strategic clarity, allowing C-level leadership to make defensible, documented determinations about which systems require high-risk compliance infrastructure and which do not.
The Classification Framework: Three Steps To Strategic Clarity
The EU AI Act’s classification system rests on three sequential decision points. This framework converts regulatory ambiguity into a defensible, documented methodology that C-level executives can implement across their organization.
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STEP 1: DETERMINE IF YOUR SYSTEM IS HIGH-RISK UNDER ARTICLE 6
The EU AI Act defines high-risk systems through two distinct pathways in Article 6. Your system is high-risk if it meets either criterion. Both must be checked.
STEP 1A: THE SAFETY-CRITICAL TEST (ARTICLE 6(1))
Is your AI system a safety component within a regulated product that must undergo third-party conformity assessment under existing EU product safety legislation?
Examples include:
- AI used in medical devices (pacemakers, diagnostic imaging, chemotherapy dosage calculation)
- AI components in aviation systems (aircraft collision avoidance, autopilot)
- AI in machinery subject to EU machinery directives
- AI in automotive systems (autonomous braking, collision detection)
- AI in rail or maritime safety systems
If YES: Your system is high-risk. Proceed to Step 2 (Article 6(3) derogation check).
Critical Output of Step 1
If YES to either 1A or 1B: Your system is high-risk. Proceed immediately to Step 2.
If NO to both 1A and 1B: Your system is not high-risk under the AI Act’s risk classification framework. However, specific transparency obligations still apply to certain categories of non-high-risk systems under Article 50:
Mandatory Transparency Obligations Apply to These Three System Types:
AI Systems Interacting Directly with Natural Persons (Article 50(1))
Your system must ensure that users are informed they are interacting with an AI system, unless this is obvious from context. Examples include chatbots, virtual assistants, and conversational AI systems. Exception: Law enforcement systems authorized to detect, prevent, investigate, and prosecute criminal offences (unless available for the public to report a crime).Emotion Recognition Systems (Article 50(2a))
Deployers must inform natural persons exposed to emotion recognition systems about the system’s operation. Exception: Systems legally authorized for crime investigation, subject to appropriate safeguards.Biometric Categorisation Systems (Article 50(2))
Deployers must inform natural persons exposed to biometric categorisation systems about the system’s operation. Exception: Systems legally authorized for crime investigation, subject to appropriate safeguards.
Additional Transparency: AI-Generated or Manipulated Content (Article 50(1a))
Systems that generate or manipulate synthetic audio, image, video, or text content must mark outputs in machine-readable format as artificially generated or manipulated. Exception: Systems performing standard assistive editing functions or where content undergoes human editorial review.
No Specific AI Act Obligations Apply If Your System:
Falls outside these four transparency categories (e.g., spam filters, internal recommender systems, backend automation without direct human interaction). However, such systems remain subject to general EU legislation including GDPR, the Digital Services Act, and sector-specific requirements.
Penalty Structure: Non-compliance with Article 50 transparency obligations can result in penalties reaching €15 million or 3% of worldwide annual turnover under Article 99.
Step 2: Article 6(3) Derogation Check - The Four Specific Functional Exceptions
If Step 1 confirmed your system is high-risk (meets either Article 6(1) or 6(2)), the critical question becomes: Does your system qualify for one of the four specific derogations under Article 6(3)? These exemptions are the only legitimate pathway from high-risk to a reduced compliance burden.
Article 6(3) establishes a foundational principle: An AI system in Annex III shall not be considered high-risk where it does not pose a significant risk of harm to health, safety, or fundamental rights, including by not materially influencing the outcome of decision-making.
Four specific functional conditions permit this downgrade:
Derogation 1: Narrow Procedural Task (Article 6(3)(a))
Your AI system is intended to perform a narrow procedural task that does not materially influence the substantive outcome of a broader process.
Critical test: Does the system merely facilitate or assist an administrative process, or does it influence the substantive result?
Examples:
An AI system that coordinates employee meeting schedules without analyzing scheduling patterns
A system that routes documents to the correct department without influencing the decision-making process
An AI that automates deadline calculation or payment processing
Why this matters: The system must be genuinely narrow in scope - focused on a specific, limited administrative function - rather than contributing to the decision-making logic of a high-risk use case.
Derogation 2: Improve Previously Completed Human Activity (Article 6(3)(b))
Your AI system is intended to improve the result of a previously completed human activity, without replacing or influencing the human assessment that already occurred.
Critical test: Does the system enhance or refine work that a human has already decided upon, or does it influence the initial human decision?
Examples:
An AI system that improves the presentation or organization of a human-finalized decision
A system that enhances the formatting or clarity of human-completed work
An AI that refines data or documentation after a human has already made the substantive decision
Why this matters: The human decision must be complete before the AI system intervenes. The AI cannot be part of the decision-making process itself.
Derogation 3: Detect Decision-Making Patterns Without Influence (Article 6(3)(c))
Your AI system is intended to detect decision-making patterns or deviations from prior decision-making patterns and is not meant to replace or influence the previously completed human assessment without proper human review.
Critical test: Does the system merely alert humans to anomalies or inconsistencies for their consideration, or does it autonomously influence decisions?
Examples:
An AI system that flags unusual transaction patterns for human review in financial services
A system that detects consistency deviations in judicial decisions but requires human review before any action
An AI that identifies outlier cases for human investigation and determination
Why this matters: Human review is mandatory. The AI provides information; humans make the consequential determination. The system cannot autonomously replace or influence human judgment without explicit human intervention.
Derogation 4: Preparatory Task to Assessment (Article 6(3)(d))
Your AI system is intended to perform a preparatory task to an assessment relevant to the high-risk use cases listed in Annex III.
Critical test: Does the system prepare information for human assessment, or does it make the substantive assessment itself?
Examples:
An AI system that creates summaries or chronologies of facts to support human decision-making
A system that searches and retrieves relevant case law or precedents for human review
An AI that organizes and presents data for human analysis in employment, credit, or justice contexts
Why this matters: The system must be genuinely preparatory - gathering, organizing, or presenting information - without making substantive determinations about individuals or decisions.
The Profiling Override: Eliminates All Four Derogations
Critical rule: Regardless of which derogation your system might qualify for, if the AI system performs profiling of natural persons, it is automatically high-risk and cannot benefit from any Article 6(3) derogation.
Profiling includes any system that analyzes, evaluates, or predicts individual-level characteristics such as:
Personality, behavior, or psychological traits
Performance potential or reliability
Trustworthiness or suitability scores
Individual risk assessment or predictive attributes
The derogations do not apply to profiling systems. This is non-negotiable.
Output of Step 2
If your system qualifies for one of these four derogations AND does not profile individuals: Proceed to Step 3 (Documentation and Enforcement). Your compliance burden is significantly reduced.
If your system does not qualify for any derogation, or if it profiles individuals: Your system is high-risk, and you must implement the full compliance infrastructure outlined in Articles 8-15 (risk management systems, data governance, technical documentation, human oversight).
STEP 3: THE PROFILING VETO – THE OVERRIDE THAT ELIMINATES ALL DEROGATIONS
This is where most organizations fail. Even if your system qualifies for a derogation under Article 6(3), a single critical condition overrides all exemptions: profiling.
What Constitutes Profiling Under the AI Act?
Any AI system that analyzes, evaluates, or predicts characteristics about an individual - personality, behavior, performance, reliability, or any other individual-level attribute—is classified as profiling. This includes:
Employee productivity analysis or performance prediction
Behavioral risk assessment or predictive profiling of individuals
Personality inference or psychological characteristic evaluation
Reliability or trustworthiness scoring
Suitability or performance potential prediction
Any system that characterizes or predicts individual-level attributes based on data
The Critical Rule: Profiling Eliminates All Derogations
If your AI system profiles individuals, it is automatically high-risk, regardless of whether it otherwise qualifies for an Article 6(3) derogation.
This is not a soft recommendation. This is a structural override. The profiling exception supersedes all derogations because profiling systems inherently make consequential determinations about individuals, even if those determinations support rather than replace human decisions.
Concrete Example: The Calendar AI Case
Consider an AI system that coordinates employee meeting schedules (procedural task, qualifies for Derogation 1). This system appears minimal-risk on its surface - it merely schedules meetings. However, if the organization subsequently adds a feature that analyzes meeting patterns to evaluate employee productivity or predict performance characteristics, that single feature addition eliminates the procedural task derogation entirely. The system has become a profiling system and is now high-risk, triggering full compliance requirements.
This distinction is not theoretical—it reflects how organizations incrementally add capabilities to systems without recognizing that a seemingly minor feature addition changes the system’s entire compliance classification.
Output of Step 3
If your system profiles individuals: Your system is high-risk, regardless of Step 2 findings. Full compliance infrastructure (Articles 8-15) is mandatory.
If your system does not profile individuals: Your classification determination is complete. The system qualifies for the derogation identified in Step 2, and your compliance obligations are reduced accordingly.
DOCUMENTATION AND REGISTRATION: THE €7.5 MILLION COMPLIANCE GAP
Accurate classification alone is insufficient. Article 6(4) imposes a critical requirement that many organizations overlook entirely:
For any AI system you determine to be exempt from high-risk classification, you must:
Document your exemption assessment in writing, explaining which Article 6(3) derogation applies and why the system qualifies
Register the system in the EU AI Database prior to market placement or putting the system into service
Maintain this documentation for regulatory inspection
Failure to meet these documentation and registration requirements triggers penalties reaching €7.5 million under Article 99 for providing incomplete or misleading information to regulators.
This creates a compliance asymmetry: organizations that accurately classify systems as high-risk and implement full compliance infrastructure may avoid €7.5M penalties, while organizations that attempt to apply exemptions without proper documentation face €7.5M exposure regardless of whether their technical classification is correct.
The Strategic Implication
The €7.5 million penalty for documentation failures creates a dual liability structure:
Classification error + no documentation = €7.5 million penalty (Article 99)
Classification error + inadequate high-risk compliance = €20 million or €35 million penalty (depending on violation type)
This means that even if an organization correctly identifies a system as high-risk but fails to document its classification rationale, it faces significant penalties. Conversely, organizations that properly document why a system qualifies for an exemption create a defensible record should regulators dispute the classification.
Why Classification Determines Your Entire Financial Exposure
Understanding the three-step framework reveals why classification accuracy is existentially consequential. The framework determines your organization’s compliance trajectory, budget allocation, and penalty exposure.
The Waste Trap: Overcompliance and €6,000-€7,000 Per Misclassified System
When organizations misclassify a minimal-risk system as high-risk, they trigger unnecessary compliance infrastructure. High-risk systems require:
Comprehensive risk management systems (Article 9)
Extensive technical documentation (Article 11, often 100+ pages per system)
Continuous monitoring and quality assurance (Article 10)
Regular audits and conformity assessments
Data governance frameworks
Transparency and logging requirements
Human oversight measures
Cost differential: Implementing high-risk compliance infrastructure for a system that qualifies for minimal-risk status costs an average of €6,000 to €7,000 per system in direct compliance expenses, according to compliance assessment data. When accounting for internal time allocation, governance restructuring, and ongoing monitoring costs, the true expense multiplies significantly.
For organizations deploying dozens or hundreds of AI systems, overcompliance becomes a budget killer. A mid-market organization with 50 systems that misclassifies 10 as high-risk when they qualify for exemptions faces €60,000-€70,000 in direct wasted compliance capital, plus substantial internal overhead. This capital could have been invested in competitive innovation, market expansion, or additional security infrastructure.
The Exposure Trap: Undercompliance and €20-€35 Million Per High-Risk System Violation
When organizations underclassify actual high-risk systems - whether through misapplication of Article 6(3) derogations or failure to recognize profiling—they deploy systems without the required governance infrastructure. The consequences are severe.
Article 99 Penalty Structure for High-Risk Obligation Breaches:
Up to €20 million or 4% of worldwide annual turnover for violations of data governance and other high-risk requirements (Article 10)
Up to €35 million or 7% of worldwide annual turnover for violations involving prohibited AI practices (Article 5)
What triggers these penalties?
Failure to implement adequate risk management systems
Inadequate data governance or quality assurance
Missing or incomplete technical documentation
Inadequate transparency and human oversight mechanisms
Failure to maintain audit logs or event traceability
Financial sector precedent: Financial services organizations that deployed AI systems without proper high-risk classification and compliance infrastructure faced average penalties of $35.2 million under AI Act enforcement frameworks. These penalties are cumulative and can apply per system.
For an organization deploying 10 misclassified high-risk systems without adequate compliance infrastructure, the cumulative penalty exposure reaches €200-€350 million. This transforms compliance from a regulatory burden into an existential business risk.
The GDPR Precedent: How the AI Act Escalates Regulatory Enforcement
Understanding the classification framework requires recognizing how the AI Act fundamentally differs from GDPR - and how that difference creates both increased complexity and accelerated enforcement.
The GDPR Model: Binary Data Protection
GDPR enforces a binary principle: personal data is either protected or it is not. Once an organization identifies that a system processes personal data, the compliance framework is largely standardized. Data protection obligations apply across the board, regardless of context.
GDPR generated €1.6 billion in fines over its first four years, establishing a precedent for aggressive enforcement as regulators gained enforcement experience. This historical precedent matters: it demonstrates that EU regulators will pursue sustained, escalating enforcement campaigns against organizations that misinterpret regulatory requirements.
The AI Act Model: Contextual Risk Classification
The AI Act enforces a contextual risk principle: compliance obligations depend on the system’s use case, the consequentiality of its decisions, and the populations affected. This requires organizations to make nuanced, case-specific determinations about which systems trigger which compliance tiers.
Why this matters: GDPR’s binary approach meant that once an organization identified a data processing activity, compliance requirements were relatively predictable. The AI Act’s contextual approach means that two organizations deploying nearly identical AI systems might face entirely different compliance obligations based on their specific use cases and how they’ve configured the system’s decision-making authority.
This contextual complexity creates enforcement risk: regulators may dispute an organization’s classification determination, arguing that specific technical features or deployment contexts trigger high-risk status.
Unlike GDPR, where “personal data” is an objective determination, “high-risk” under the AI Act involves subjective judgment that regulators will scrutinize retrospectively.
Escalated Penalty Structure
The AI Act’s maximum penalties rival and exceed GDPR’s:
GDPR: Up to €20 million or 4% of global annual turnover
AI Act: Up to €35 million or 7% of global annual turnover (for high-risk violations and prohibited practices)
Critical difference: AI Act penalties accumulate per system. An organization deploying 10 misclassified high-risk systems without adequate compliance infrastructure faces 10 independent violation streams, each capable of triggering €20-€35 million in penalties. GDPR enforcement typically aggregates violations into a single penalty structure.
The AI Act’s per-system penalty architecture creates exponential financial exposure.
The Implementation Imperative: Why Your Timeline Is Actually Shorter Than You Think
The critical strategic insight is recognizing the distinction between headline deadlines and implementation constraints.
The Enforcement Timeline
The EU AI Act’s enforcement calendar includes three critical dates:
August 2, 2025 (Already Active): Transparency and governance requirements for general-purpose AI systems (GPAI) are already in effect
August 2, 2026: Classification documentation and EU database registration requirements take effect. Organizations must have completed classification assessments and documented exemption determinations
August 2, 2027 (Full Enforcement): Full high-risk compliance, including risk management systems, data governance frameworks, and technical documentation, must be operational
The Real Constraint: The August 2, 2026 Documentation Deadline
While the August 2, 2027 date represents full compliance, the August 2, 2026 deadline is the actual decision point. At this date, organizations must have:
Completed classification assessments for all deployed AI systems
Documented exemption determinations (for systems claiming Article 6(3) derogations)
Registered systems in the EU AI Database
Why this matters: An organization that hasn’t completed its classification assessment by August 2, 2026 enters August 2, 2027 in a state of non-compliance by definition. It cannot claim to have implemented high-risk compliance infrastructure if it hasn’t yet classified which systems are high-risk.
The Exponential Cost of Delayed Action
Consider the realistic implementation timeline:
Phase 1: Conduct classification assessment across all AI systems
Phase 2: Design and implement risk management systems and data governance frameworks
Phase 3: Deploy, test, audit, and certify compliance infrastructure
Organizations that delay 6 months compress the timeline significantly, cutting Phase 1 and Phase 2 timelines in half. This creates cascading consequences:
Rushed classification assessments increase misclassification risk (creating both waste and exposure traps)
Compressed implementation timelines prevent proper testing and validation
Emergency procurement of compliance infrastructure increases costs by 30-40%
Increased regulatory scrutiny due to late-stage changes and documentation gaps
The strategic imperative: Organizations that complete classification assessments now—before August 2, 2026 - gain a competitive advantage of 12+ months in implementation timeline, testing, and certification. Those that delay surrender market advantages to competitors who are already preparing compliant AI deployments.
Moving from Classification to Action: The Strategic Imperative
The three-step classification framework (Article 6(1) → Article 6(2) → Article 6(3) Derogations → Profiling Veto) converts regulatory ambiguity into a defensible, documented decision methodology. But the framework only creates value when implemented systematically across your organization.
The strategic moves your leadership team must make now:
Conduct a complete system inventory: Catalog all AI systems across business functions, identifying which fall under Article 6(1) (safety components) or Annex III’s 24 high-risk categories
Apply the derogation framework: For each Article 6(1) or Annex III system, determine whether it qualifies for an Article 6(3) derogation and document the rationale
Implement the profiling veto: Flag any system that profiles individuals, regardless of derogation status, and reclassify as high-risk
Document exemption determinations: For any system claiming an exemption, prepare written documentation explaining which derogation applies and why
Register in the EU AI Database: Prior to August 2, 2026, register all systems in the EU AI Database
Plan implementation: For systems classified as high-risk, begin designing risk management systems (Article 9), data governance frameworks (Article 10), and technical documentation (Article 11)
The time until the August 2, 2026 deadline represents your strategic window for action. Organizations that complete this classification assessment and documentation process by mid-2026 will have 12 months to implement compliant infrastructure before full enforcement. Organizations that delay this assessment compress timelines, increase costs, and multiply misclassification risk.
Conclusion: Classification as Competitive Advantage
The EU AI Act’s complexity stems from its contextual, risk-based approach to AI governance—a fundamental departure from GDPR’s binary data protection model. This complexity creates both a compliance burden and a strategic opportunity.
Organizations that master the three-step classification framework—Article 6(1) safety-critical test, Article 6(2) Annex III categorization, Article 6(3) derogation assessment, and profiling veto—transform regulatory ambiguity into strategic clarity. They avoid the dual financial trap of overcompliance waste and undercompliance exposure. More importantly, they position themselves as market leaders in compliant AI deployment.
With the August 2, 2026 documentation deadline only months away, the classification decision is no longer theoretical. It is the determinant of your organization’s regulatory compliance, financial exposure, and competitive positioning in an AI-governed market.
The question is no longer “Should we classify our AI systems?” The question is: “Do we classify them correctly, defensibly, and with full documentation - or do we face the consequences of ambiguity?”
DISCLAIMER
This article provides educational guidance on EU AI Act classification methodology and compliance frameworks. It does not constitute legal advice, regulatory interpretation, or compliance certification.
Classification determinations under the EU AI Act are the responsibility of your organization. The methodologies, frameworks, and examples provided in this article are for informational purposes only and should be reviewed by qualified legal counsel familiar with your specific use cases and jurisdiction.
Quantum Coherence LLC and the author:
Do not provide legal advice or regulatory compliance determinations
Do not certify conformity assessments or issue declarations of compliance
Are not responsible for classification decisions made by organizations using this framework
Recommend organizations consult qualified legal counsel before making final classification determinations
The penalty figures, compliance costs, and regulatory timelines referenced in this article are based on publicly available EU AI Act text and implementation guidance as of November 2025. Regulatory interpretations may evolve as enforcement proceeds.
For specific compliance questions regarding your AI systems, consult qualified legal counsel specializing in EU AI Act implementation.
Regulatory and Legal Disclaimer
This article provides educational analysis of the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) and related enforcement mechanisms. The content is based on:
The official EU AI Act text as published in the Official Journal of the European Union
Publicly available leaked drafts of the EU AI Act simplification proposal (November 2025)
Market surveillance regulations under Regulation (EU) 2019/1020
Publicly available enforcement guidance and implementation timelines as of November 2025
This article does not constitute legal advice, regulatory interpretation, or compliance certification.
EU AI Act implementation involves complex legal determinations that depend on:
Specific AI system architectures and intended purposes
Organizational context and deployment environments
Jurisdiction-specific enforcement priorities and interpretations
Evolving regulatory guidance from the European Commission and Member State authorities
Organizations should consult qualified legal counsel specializing in EU AI Act compliance before making classification determinations, compliance investments, or deployment decisions.
Limitation of Liability
The author, Violeta Klein, and Quantum Coherence LLC:
Do not provide legal advice or regulatory compliance determinations
Do not certify conformity assessments or issue declarations of compliance
Are not responsible for classification decisions, compliance strategies, or deployment choices made by organizations using the frameworks described in this article
Make no representations or warranties regarding the accuracy, completeness, or currency of information presented
Disclaim all liability for any direct, indirect, incidental, consequential, or punitive damages arising from reliance on this content
Penalty figures, compliance costs, timelines, and enforcement scenarios referenced in this article are illustrative examples based on regulatory text and publicly available information as of November 2025. Actual penalties, costs, and enforcement actions will vary based on specific circumstances, Member State implementation, and regulatory discretion.
Dynamic Regulatory Environment Notice
The EU AI Act regulatory landscape is rapidly evolving. Key developments that may affect the analysis in this article include:
February 2, 2026: European Commission publication of Article 6 classification guidelines and practical implementation examples
Ongoing: Member State designation of Market Surveillance Authorities and development of enforcement procedures
Ongoing: European AI Office publication of codes of practice, technical standards, and harmonized implementation guidance
Ongoing: Court of Justice of the European Union interpretations of AI Act provisions through enforcement actions and legal challenges
Organizations must maintain dynamic compliance programs that incorporate new regulatory guidance, enforcement precedents, and technical standards as they are published. Static compliance frameworks based solely on current regulatory text will become outdated as implementation guidance evolves.
Professional Credentials Disclosure
Violeta Klein holds the following professional certifications:
CISSP (Certified Information Systems Security Professional) - ISC², credential ID 6f921ada-2172-410e-8fff-c31e1a032818, valid through July 2028
CEFA (Certified European Financial Analyst) - EFFAS, issued 2009
These certifications demonstrate technical expertise in information security and financial analysis. They do not constitute legal credentials or regulatory authority to provide legal advice on EU AI Act compliance.
The analysis in this article represents the author’s professional interpretation of publicly available regulatory materials and does not constitute official guidance from regulatory authorities, legal opinions, or compliance certifications.
Source Citations and References
This article references the following primary sources:
Regulation (EU) 2024/1689 - Artificial Intelligence Act, Official Journal of the European Union
Regulation (EU) 2019/1020 - Market surveillance and compliance of products
European Commission Leaked Draft Proposal - Digital Omnibus on AI Simplification (November 2025)
Specific Article References: Articles 3, 5, 6, 9, 10, 11, 12, 14, 15, 17, 26, 50, 57, 72, 73, 74-78, 99, 100
Official EU AI Act resources:
EUR-Lex: Official EU legal database
European Commission AI Act webpage: digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai
European AI Office: ai-office.ec.europa.eu
For binding legal interpretations and compliance obligations specific to your organization, consult:
Qualified legal counsel specializing in EU AI Act compliance
Your designated Member State Market Surveillance Authority
Notified bodies for conformity assessment (for high-risk systems)
Content Update Policy
This article reflects the regulatory landscape as of November 03, 2025. Significant regulatory developments after this date may affect the accuracy of timelines, penalty structures, or enforcement mechanisms described herein.
Readers should verify:
Current enforcement timelines and Member State authority designations
Publication status of European Commission guidelines (particularly Article 6 classification guidance)
Updates to the simplification proposal and final legislative adoption
Enforcement precedents and penalty applications by Market Surveillance Authorities