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Duration 14 hours
Course Outline
The EU AI Act: Structure and Regulatory Basis
- Key objectives, scope, and core principles.
- Definitions and criteria for classifying AI systems.
- Responsibilities assigned to various stakeholders.
Risk Classification and Compliance Standards
- Banned AI systems and preventive controls.
- High-risk systems and the necessity for mandatory documentation.
- Standards for limited-risk and minimal-risk systems.
Building AI Governance and Internal Policies
- Developing internal governance frameworks.
- Structuring oversight mechanisms and reporting hierarchies.
- Managing document control and the policy lifecycle.
Technical and Organizational Safeguards
- Implementing risk management systems for continuous evaluation.
- Establishing human oversight mechanisms.
- Ensuring data governance, robustness, and cybersecurity.
Compliance Documentation and Record Retention
- Technical documentation requirements for high-risk systems.
- Obligations regarding log retention and traceability.
- Retention of materials related to conformity assessments.
Monitoring, Auditing, and Reporting Mechanisms
- Internal audit procedures for AI supervision.
- Reporting duties to regulatory authorities and stakeholders.
- Requirements for corrective actions and incident response.
Third-Party, Vendor, and Supply-Chain Compliance
- Assessing AI tools and claims provided by vendors.
- Contractual requirements and compliance clauses.
- Ongoing monitoring and re-evaluation of external AI services.
Implementing Continuous Compliance
- Developing a long-term compliance strategy.
- Fostering cross-functional cooperation with IT, legal, and management teams.
- Staying prepared for evolving regulatory changes.
Wrap-up and Future Actions
Requirements
- Working knowledge of regulatory or compliance procedures.
- Practical experience in organizational risk management.
- Understanding of documentation and audit workflows.
Intended Audience
- Governance and risk officers.
- Compliance and legal specialists.
- Internal audit and quality assurance teams.
