The European Union's Artificial Intelligence Act, which entered into force in August 2024 with phased implementation through 2027, represents the world's first comprehensive AI regulation. Like GDPR, the AI Act has extraterritorial reach that extends far beyond Europe's borders, affecting Asian businesses deploying AI systems in EU markets or impacting EU residents. This guide analyzes the AI Act's application to Asian organizations, compliance requirements, and strategic implications.
Understanding the EU AI Act's Scope
The AI Act establishes a risk-based regulatory framework categorizing AI systems by risk level and imposing corresponding obligations.
Territorial Scope (Article 2)
The AI Act applies to:
1. Providers Placing AI Systems on EU Market: Asian companies placing AI systems on the EU market or putting them into service in the EU, regardless of provider location.
2. Users of AI Systems Located in EU: AI system users (deployers) located or established in the EU.
3. Providers and Users Outside EU: Providers and users located outside the EU when:
- Output produced by the AI system is used in the EU
- AI system affects persons in the EU
Practical Implications for Asian Businesses:
Scenario 1: SaaS Platform Targeting EU Singapore SaaS company offers AI-powered HR analytics to European companies. The AI Act applies as:
- System placed on EU market
- Output (employee analytics) used in EU
- EU employees affected
Compliance required: Full AI Act obligations based on risk classification.
Scenario 2: Manufacturing AI for EU Export Japanese robotics company manufactures AI-powered industrial robots exported to EU factories. The AI Act applies as system placed on EU market.
Compliance required: Provider obligations including conformity assessment, technical documentation, CE marking.
Scenario 3: AI Development Services Indian AI development firm builds custom AI models for EU clients under contract. AI Act application depends on whether firm is provider or merely supplies components.
Compliance required: If provider, full obligations; if component supplier, contractual obligations with EU provider.
Scenario 4: Global Platform with EU Users Chinese social media platform operates globally including EU users. Recommendation algorithms and content moderation AI trigger AI Act as systems affect EU persons.
Compliance required: High-risk system obligations if large-scale profiling or content moderation meets thresholds.
Scenario 5: Pure Domestic Operations Thai e-commerce platform operates only in Thailand, processes only Thai user data, provides only Thai-language support, and does not target EU. AI Act does not apply.
Compliance required: None under AI Act (Thai domestic regulations apply).
Key Definitions
AI System (Article 3(1)): Machine-based system designed to operate with varying levels of autonomy that may exhibit adaptiveness after deployment and that, for explicit or implicit objectives, infers how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.
This broad definition covers:
- Machine learning models (supervised, unsupervised, reinforcement learning)
- Logic and knowledge-based approaches
- Statistical approaches
- Bayesian estimation, search and optimization methods
Provider (Article 3(3)): Natural or legal person, public authority, agency or other body that develops an AI system or has an AI system developed and places it on the market or puts it into service under its own name or trademark, whether for payment or free of charge.
Deployer/User (Article 3(4)): 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.
Placing on Market (Article 3(9)): First making available of an AI system on the Union market.
Making Available (Article 3(10)): Supply of an AI system for distribution or use on the Union market in the course of a commercial activity, whether in return for payment or free of charge.
Risk-Based Classification System
The AI Act categorizes AI systems into four risk levels with corresponding obligations.
Prohibited AI Practices (Article 5)
Certain AI systems are banned in the EU regardless of provider location:
1. Subliminal Manipulation: AI deploying subliminal techniques beyond person's consciousness to materially distort behavior causing or likely to cause significant harm.
Example: Advertising AI using imperceptible audio cues to influence purchasing behavior.
2. Exploitation of Vulnerabilities: AI exploiting vulnerabilities of specific groups (age, disability, social/economic situation) to materially distort behavior causing significant harm.
Example: Gaming app targeting children with AI-driven addiction mechanisms.
3. Social Scoring: AI evaluating or classifying persons based on social behavior or personal characteristics, with detrimental or unfavorable treatment unrelated to context or disproportionate to behavior.
Example: Creditworthiness AI considering social media activity unrelated to financial behavior.
4. Real-Time Remote Biometric Identification in Public: Real-time remote biometric identification systems in publicly accessible spaces for law enforcement (with narrow exceptions).
Example: Live facial recognition in shopping centers for security purposes (prohibited for private entities).
5. Predictive Policing Based on Profiling: AI assessing risk of individuals committing criminal offenses based solely on profiling or personality traits.
6. Emotion Recognition in Certain Contexts: Emotion recognition systems in workplace and education (with exceptions for medical or safety reasons).
7. Indiscriminate Scraping: Untargeted scraping of facial images from internet or CCTV footage for facial recognition databases.
Implications for Asian Businesses:
Any AI system falling into prohibited categories cannot be offered in EU regardless of benefits or safeguards. Organizations must:
- Conduct prohibited use assessment before EU market entry
- Ensure AI systems don't incorporate prohibited functionalities
- Document rationale for determining system not prohibited
- Monitor for future expansions of prohibited list
High-Risk AI Systems (Articles 6-7, Annex III)
High-risk AI systems require comprehensive compliance before EU market placement.
Definition: AI systems that pose significant risks to health, safety, or fundamental rights.
Categories:
1. Biometric Identification and Categorization:
- Remote biometric identification systems
- Biometric categorization according to sensitive attributes
2. Critical Infrastructure Management:
- AI managing critical digital infrastructure
- AI controlling water, gas, electricity, heating supply
3. Education and Vocational Training:
- AI determining educational institution access
- AI assessing students
- AI detecting prohibited behavior during tests
- AI evaluating learning level
4. Employment and Worker Management:
- AI for recruitment and worker selection
- AI making employment decisions (promotion, termination, task allocation)
- AI monitoring and evaluating worker performance and behavior
5. Access to Essential Services:
- AI evaluating creditworthiness or credit score (except fraud detection)
- AI assessing emergency response prioritization
- AI dispatching or establishing priority in emergency services
- AI evaluating eligibility for public assistance and services
6. Law Enforcement:
- AI assessing risk of individuals as crime victims
- AI for polygraph and similar tools
- AI evaluating reliability of evidence
- AI assessing recidivism risk
- AI for profiling during crime detection, investigation, prosecution
7. Migration, Asylum, Border Control:
- AI assisting authorities examining asylum/visa applications
- AI for border control verification (documents, persons)
- AI assessing security or health risk
8. Administration of Justice and Democratic Processes:
- AI assisting judicial authorities in researching and interpreting facts and law
- AI influencing democratic process outcomes
High-Risk Obligations for Providers:
Risk Management System (Article 9):
- Establish continuous, iterative risk management process
- Identify known and foreseeable risks
- Estimate and evaluate risks
- Adopt suitable risk management measures
- Test AI system and evaluate residual risk
- Eliminate or reduce risks through design and development
Data and Data Governance (Article 10):
- Training, validation, testing datasets meet quality criteria
- Relevant, representative, free of errors, complete
- Appropriate statistical properties for intended purpose
- Consider biases that may affect health, safety, or fundamental rights
- Ensure data subject to data governance and management practices
Technical Documentation (Article 11, Annex IV):
- Comprehensive documentation including:
- General description of AI system
- Detailed description of system elements and development process
- Detailed information about monitoring, functioning, and control
- Description of risk management system
- Description of changes made through lifecycle
- Performance metrics
- Validation and testing procedures
Record-Keeping (Article 12):
- Automatically generated logs enabling traceability
- Log functioning periods
- Database against which input data checked
- Input data or link to data
- Identity of natural persons involved in testing and operation
Transparency and Provision of Information to Users (Article 13):
- Instructions for use in appropriate digital or other format
- Clear, comprehensive, correct, easily accessible information
- Include intended purpose, specifications, human oversight measures
- Document expected level of accuracy, robustness, cybersecurity
Human Oversight (Article 14):
- Enable human oversight to prevent or minimize risks
- Oversight through interface design or stop button
- Ensure individuals have appropriate competence, training, authority
- Fully understand AI system capabilities and limitations
Accuracy, Robustness, Cybersecurity (Article 15):
- Achieve appropriate levels throughout lifecycle
- Address technical robustness
- Ensure resilience against errors, faults, inconsistencies
- Protect against malicious third-party attempts to alter system
Conformity Assessment (Article 43):
- Conduct conformity assessment before market placement
- Internal control (Annex VI) for most high-risk systems
- Third-party assessment for biometric systems and critical infrastructure
- Affix CE marking upon successful assessment
Registration (Article 49):
- Register high-risk AI system in EU database before market placement
- Provide name, type, intended purpose, contact details
- Update registration for substantial modifications
Post-Market Monitoring (Article 72):
- Establish and document post-market monitoring system
- Collect, document, analyze relevant data on performance
- Report serious incidents and malfunctions
- Cooperate with competent authorities
Quality Management System (Article 17):
- Documented and maintained quality management system
- Compliance with regulatory requirements
- Document examination, test, and validation procedures
- Data management procedures
- Post-market monitoring system
Limited-Risk AI Systems (Transparency Obligations)
Certain AI systems pose limited risk but require transparency to enable informed use.
Systems Subject to Transparency (Article 50):
1. AI Interacting with Humans: Chatbots, virtual assistants, and similar systems must inform users they're interacting with AI (unless obvious from context).
Example: Customer service chatbot must disclose AI nature, but advanced voice assistant clearly marketed as AI may not require disclosure.
2. Emotion Recognition or Biometric Categorization: Systems inferring emotions or categorizing individuals based on biometric data must inform affected persons.
Example: Retail analytics using facial analysis to infer customer emotions must notify customers.
3. AI-Generated Content (Deep Fakes): Systems generating synthetic audio, image, video, or text content must:
- Disclose content is artificially generated or manipulated
- Enable detection through technical solutions
- Mark content in machine-readable format
Example: AI video generator must watermark outputs and provide disclosure in content.
Exceptions:
- Authorized law enforcement detection activities
- AI systems performing auxiliary functions (standard editing, format conversion)
- Content clearly labeled as parody or artistic expression
Minimal-Risk AI Systems
AI systems not falling into prohibited, high-risk, or limited-risk categories face no specific AI Act obligations (though general law applies).
Examples:
- Spam filters
- Inventory management AI
- Recommendation systems (unless high-risk scale)
- AI-powered search engines
- Grammar checking tools
Voluntary Measures: Providers may voluntarily adopt codes of conduct, quality management, or transparency measures to build trust.
General Purpose AI Models (GPAI)
The AI Act includes specific provisions for general purpose AI models like large language models.
GPAI Model Obligations (Articles 53-56)
All GPAI Model Providers:
Technical Documentation (Article 53):
- Information on model training, data, compute
- Evaluation results and mitigation measures
- Information on capabilities and limitations
- Details of data governance measures
Transparency (Article 53):
- Prepare and make available technical documentation
- Publish summary of copyrighted content used in training
- Put in place policy to comply with EU copyright law
Downstream Provider Cooperation:
- Provide information and documentation to downstream providers
- Enable compliance with AI Act obligations
GPAI Models with Systemic Risk (Article 55):
Models with high impact capabilities posing systemic risk at Union level:
Additional Obligations:
- Adversarial testing and evaluation
- Assessment and mitigation of systemic risks
- Track, document, report serious incidents
- Ensure adequate cybersecurity protection
Systemic Risk Determination: Based on model capabilities or computational resources (cumulative compute during training exceeding 10^25 FLOPs).
Implications for Asian AI Model Developers:
Asian companies developing foundation models for EU market must:
- Maintain comprehensive technical documentation
- Publish copyright transparency reports
- Implement data governance for training data
- Assess systemic risk for large models
- Provide downstream provider support
- Monitor for security incidents
Compliance Obligations by Role
For Asian Providers (Developers/Vendors)
High-Risk AI System Providers Must:
- Implement risk management system
- Ensure data quality and governance
- Create comprehensive technical documentation
- Implement automatic logging and record-keeping
- Design for human oversight
- Achieve accuracy, robustness, cybersecurity
- Conduct conformity assessment
- Affix CE marking
- Register in EU database
- Provide user instructions
- Establish post-market monitoring
- Report serious incidents
- Implement quality management system
GPAI Model Providers Must:
- Create and maintain technical documentation
- Publish copyright content summary
- Implement copyright compliance policy
- Cooperate with downstream providers
- (If systemic risk) Conduct adversarial testing, risk mitigation, incident reporting
Limited-Risk AI Providers Must:
- Implement appropriate transparency measures
- Disclose AI interaction, emotion recognition, or synthetic content
- Enable detection of synthetic content
For Asian Deployers (Users)
High-Risk AI System Deployers Must:
- Use systems according to instructions
- Ensure human oversight
- Monitor operation for risks
- Report serious incidents to provider
- Keep automatically generated logs
- Conduct fundamental rights impact assessment (if required)
- Implement appropriate technical and organizational measures
- Inform provider and competent authority of serious incidents
Limited-Risk AI Deployers Must:
- Ensure transparency obligations fulfilled
- Inform users of AI interaction
- Verify synthetic content disclosure
For Importers and Distributors
Importers Must:
- Verify provider completed conformity assessment
- Verify provider prepared technical documentation
- Verify AI system bears CE marking
- Verify provider provided instructions and contact details
- Ensure appropriate storage and transport conditions
- Register in EU database (if provider hasn't)
- Provide competent authorities with information on request
Distributors Must:
- Verify AI system bears CE marking
- Verify provider and importer complied with obligations
- Verify instructions and contact details provided
- Ensure storage and transport don't compromise compliance
- Report suspected non-compliance to competent authorities
EU Representative Requirement (Article 23-24)
Non-EU providers of high-risk AI systems or GPAI models must appoint written EU representative unless:
- Provider already established in EU
- System exclusively for export
- Minimal risk system
Representative Responsibilities:
- Verify conformity assessment conducted
- Keep copy of technical documentation and conformity declaration
- Provide information to competent authorities
- Cooperate on investigation or measures
- May be natural person or legal entity established in EU
Enforcement and Penalties
Administrative Fines (Article 99)
The AI Act establishes tiered penalties:
Tier 1: Up to €35 million or 7% of global annual turnover (whichever higher):
- Providing prohibited AI system
- Non-compliance with data requirements (Article 10)
- Violation of transparency obligations for GPAI with systemic risk
Tier 2: Up to €15 million or 3% of global annual turnover:
- Non-compliance with high-risk AI obligations (except data requirements)
- Incorrect, incomplete, misleading information to authorities
- Non-compliance with AI Office requests or investigatory powers
Tier 3: Up to €7.5 million or 1.5% of global annual turnover:
- Providing incorrect, incomplete, misleading information to notified bodies
- Violation of transparency obligations (Article 50)
SME Considerations: For SMEs (including startups), fines are capped at lower amounts:
- Tier 1: Lesser of 7% turnover or €35 million
- Tier 2: Lesser of 3% turnover or €15 million
- Tier 3: Lesser of 1.5% turnover or €7.5 million
Factors Affecting Penalty Levels
Aggravating Factors:
- Intentional or negligent non-compliance
- Previous infringements
- Refusal to cooperate with authorities
- High potential or actual harm
- Involvement of vulnerable groups
Mitigating Factors:
- Effective compliance management systems
- Cooperation with authorities
- Self-reporting of violations
- Prompt remediation
- Limited scope or duration of non-compliance
Enforcement Actions
Competent authorities may:
- Order cessation of AI system placement or withdrawal from market
- Temporarily restrict or suspend AI system availability
- Require modification of AI system
- Conduct audits and inspections
- Access technical documentation and source code
- Order provider to communicate risk to users
- Initiate product recall
Strategic Compliance Roadmap for Asian Businesses
Phase 1: Applicability Assessment (Month 1)
Determine AI Act Application:
- Do you place AI systems on EU market?
- Do you deploy AI systems with outputs used in EU?
- Do your AI systems affect EU persons?
- Document applicability determination
Identify Roles:
- Are you provider, deployer, importer, distributor?
- Do you develop components for other providers?
- Do you offer GPAI models?
Inventory AI Systems:
- Catalog all AI systems potentially subject to AI Act
- Document system purposes, capabilities, data sources
- Identify EU market presence or impact
Phase 2: Risk Classification (Month 2)
Classify Each AI System:
- Prohibited (immediate market withdrawal if applicable)
- High-risk (compare against Annex III categories)
- Limited-risk (transparency obligations)
- Minimal-risk (no specific obligations)
Document Classification Rationale:
- Detailed analysis of system against definitions
- Risk assessment considering potential harms
- Legal review of classification conclusions
Prioritize Compliance:
- Prohibited systems: Immediate action
- High-risk systems: Comprehensive compliance program
- Limited-risk: Transparency implementation
- Minimal-risk: Monitor for reclassification
Phase 3: Gap Analysis (Months 2-3)
For high-risk and GPAI systems:
Risk Management:
- Current risk identification and mitigation processes
- Documentation completeness
- Continuous improvement mechanisms
Data Governance:
- Training data quality, representativeness, bias
- Data sourcing and provenance
- Validation and testing data
Technical Documentation:
- Existence and completeness of required documentation
- Version control and maintenance
- Accessibility for competent authorities
Logging and Record-Keeping:
- Automatic logging capabilities
- Log retention periods
- Traceability mechanisms
Human Oversight:
- Interface design for oversight
- Training and competence of oversight personnel
- Authority to intervene or stop system
Accuracy, Robustness, Security:
- Performance metrics and monitoring
- Resilience testing
- Cybersecurity controls
Transparency:
- User instructions completeness
- Disclosure adequacy
- Understandability for intended users
Phase 4: Compliance Implementation (Months 4-12)
Establish Governance:
- Appoint AI compliance officer or team
- Define AI governance framework
- Allocate resources and budget
- Appoint EU representative (if required)
Implement Technical Measures:
- Develop or enhance risk management system
- Improve data quality and governance
- Implement logging and traceability
- Design human oversight mechanisms
- Enhance accuracy, robustness, cybersecurity
- Deploy transparency measures
Create Documentation:
- Technical documentation (Annex IV)
- Risk management documentation
- Data governance records
- Conformity assessment reports
- Instructions for use
- Quality management system documentation
Conduct Conformity Assessment:
- Internal assessment for most high-risk systems
- Third-party notified body assessment (if required)
- Prepare EU declaration of conformity
- Affix CE marking
Register Systems:
- Register in EU AI system database
- Provide required information
- Maintain registration currency
Phase 5: Operationalization (Months 10-14)
Post-Market Monitoring:
- Establish monitoring plan and processes
- Collect performance and incident data
- Analyze trends and anomalies
- Report serious incidents
User Support:
- Provide comprehensive instructions
- Offer training to deployers
- Establish support channels
- Address user questions and issues
Supply Chain Management:
- Ensure importer/distributor compliance
- Coordinate with EU representative
- Manage component supplier obligations
Training and Awareness:
- Train development teams on AI Act requirements
- Educate sales and marketing on compliance claims
- Prepare customer-facing teams for inquiries
- Conduct regular refresher training
Phase 6: Continuous Compliance (Ongoing)
Monitoring and Review:
- Track regulatory guidance and enforcement
- Monitor system performance and incidents
- Review and update risk assessments
- Conduct periodic internal audits
System Lifecycle Management:
- Assess substantial modifications for re-assessment
- Update documentation for system changes
- Re-classify systems if use cases evolve
- Maintain conformity throughout lifecycle
Regulatory Engagement:
- Participate in stakeholder consultations
- Engage with European AI Office
- Join industry associations and working groups
- Monitor harmonized standards development
Strategic Considerations
Market Access vs. Compliance Cost
Asian businesses must weigh EU market opportunity against compliance investment:
High Compliance Cost Scenarios:
- Multiple high-risk AI systems requiring assessment
- Novel AI technologies without established best practices
- Limited EU revenue potential
- Resource-constrained organizations
Strategies:
- Prioritize EU market entry for high-value systems
- Consider partnerships with EU-established entities
- Leverage compliance as competitive differentiator
- Explore regulatory sandboxes for innovative AI
- Phase market entry starting with lower-risk systems
Build vs. Buy Compliance
Build Internally:
- Advantages: Deep organizational knowledge, long-term capability, integration with development
- Disadvantages: Resource intensive, requires expertise, slower initial implementation
- Best for: Large organizations, long-term EU strategy, multiple AI systems
Buy External Support:
- Advantages: Immediate expertise, faster implementation, reduced internal burden
- Disadvantages: Ongoing costs, dependency on external parties, less organizational learning
- Best for: Smaller organizations, limited AI portfolio, near-term market entry needs
Hybrid Approach:
- Core compliance expertise internal
- Specialized assessments external (e.g., third-party conformity)
- Legal interpretation external
- Implementation and operations internal
Competitive Positioning
AI Act compliance can be competitive advantage:
Trust and Credibility:
- Demonstrate commitment to responsible AI
- Build confidence with EU customers and partners
- Differentiate from non-compliant competitors
Market Readiness:
- Early compliance enables faster market entry
- Positions for enterprise and government contracts
- Supports long-term EU market strategy
Global Standards Alignment:
- AI Act influencing global AI regulation
- Compliance positions for other markets
- Reduces adaptation needs for future regulations
Conclusion
The EU AI Act represents a paradigm shift in AI regulation with significant implications for Asian businesses. Its extraterritorial reach means organizations placing AI systems on EU markets, affecting EU persons, or deploying systems in EU must comply with comprehensive requirements based on risk classification.
For Asian businesses, the AI Act presents both challenges and opportunities. Compliance requires significant investment in risk management, data governance, transparency, and documentation. However, it also offers competitive advantages through enhanced trust, market readiness, and alignment with emerging global standards.
Success requires early assessment of applicability, accurate risk classification, structured compliance implementation, and strategic decisions about market entry timing and approach. Organizations that proactively embrace AI Act compliance will be well-positioned to succeed in the EU market and navigate the evolving global AI regulatory landscape.
Explore related compliance requirements in our GDPR guide for Asian businesses.
Need expert guidance on EU AI Act compliance for your organization? Contact Pertama Partners for specialized advisory services.
Frequently Asked Questions
Yes, the EU AI Act applies extraterritorially to Asian businesses when they: (1) place AI systems on the EU market or put them into service in the EU; (2) are users of AI systems located in the EU; or (3) are located outside the EU but their AI system's output is used in the EU or affects persons in the EU. For example, a Singapore SaaS company offering AI-powered analytics to European companies must comply, as must a Japanese robotics manufacturer exporting to EU factories. Physical EU presence is not required for AI Act applicability.
The AI Act bans certain AI systems regardless of benefits: subliminal manipulation distorting behavior; exploitation of vulnerable groups' vulnerabilities; social scoring causing detrimental treatment; real-time remote biometric identification in public spaces (with narrow law enforcement exceptions); predictive policing based solely on profiling; emotion recognition in workplace and education (except medical/safety); and indiscriminate facial image scraping. Asian businesses must ensure their AI systems don't incorporate prohibited functionalities before EU market entry, as no safeguards can legitimize prohibited systems.
High-risk AI systems are those posing significant risks to health, safety, or fundamental rights, listed in Annex III across eight categories: biometric identification; critical infrastructure; education and training; employment and worker management; access to essential services (credit scoring, emergency response, public assistance); law enforcement; migration and border control; and administration of justice. Examples include AI recruitment systems, credit scoring algorithms, educational assessment tools, and worker performance monitoring. High-risk classification triggers comprehensive compliance obligations including risk management, data governance, conformity assessment, and CE marking.
GPAI models are AI models like large language models trained for general purposes that can be adapted to various downstream applications. All GPAI providers must: create technical documentation covering training, data, compute, and capabilities; publish summaries of copyrighted training content; implement copyright compliance policies; and cooperate with downstream providers. GPAI models with systemic risk (high impact capabilities or over 10^25 FLOPs compute) face additional obligations: adversarial testing, systemic risk assessment and mitigation, serious incident reporting, and adequate cybersecurity. Asian foundation model developers targeting EU must comply.
The AI Act establishes tiered fines: up to €35 million or 7% of global annual turnover (whichever higher) for prohibited AI systems or serious data requirement violations; up to €15 million or 3% for high-risk AI non-compliance; up to €7.5 million or 1.5% for transparency obligation violations. SMEs face lower caps. Factors affecting penalties include intentional vs. negligent violations, prior infringements, cooperation level, harm potential, and involvement of vulnerable groups. Beyond fines, authorities can order market withdrawal, temporary suspension, system modification, or product recall.
Non-EU providers of high-risk AI systems or GPAI models must appoint a written EU representative established in an EU Member State, unless the provider is already established in the EU or the system is exclusively for export outside the EU. The representative must verify conformity assessments, keep copies of technical documentation, provide information to competent authorities, and cooperate on investigations. Representatives do not replace provider liability but facilitate regulatory engagement and enforcement. Find representatives through legal firms, specialized providers, or potentially EU subsidiaries if appropriately structured.
Implement a phased approach: (1) Applicability assessment—determine if AI Act applies to your systems and identify your role (provider, deployer, importer); (2) Risk classification—categorize systems as prohibited, high-risk, limited-risk, or minimal-risk; (3) Gap analysis—assess current state against obligations; (4) Compliance implementation—establish governance, implement technical measures, create documentation, conduct conformity assessment, register systems, appoint EU representative if required; (5) Operationalization—establish post-market monitoring, user support, supply chain management, training; (6) Continuous compliance—monitor regulatory developments, manage system lifecycle, engage with regulators. Consider early compliance as competitive advantage.