Compliance Requirements

Compliance requirements are the sum of an organization's mandatory obligations ('requirements it has to comply with') and voluntary commitments ('requirements it chooses to comply with'). This concept is formally defined in ISO 37301:2021 (Compliance management systems). Mandatory requirements include laws and regulations like the EU AI Act or GDPR, while voluntary ones encompass international standards (e.g., ISO/IEC 42001), industry codes, and ethical commitments. Within risk management, they are a critical input for risk identification, defining the legal and ethical boundaries that cannot be crossed. Unlike 'risk appetite,' which is the level of risk an organization is willing to accept to achieve objectives, compliance requirements represent non-negotiable constraints.

Applying compliance requirements in ERM involves a systematic process. Key steps include: 1. **Identification and Inventory**: Create and maintain a 'compliance obligations register' that lists all applicable laws (e.g., EU AI Act), standards (e.g., ISO/IEC 27701), and contractual terms. 2. **Impact Analysis and Control Design**: Assess how each requirement affects business processes and AI systems, then design and implement corresponding controls. For instance, to meet GDPR's 'right to be forgotten,' an AI system must have a technical mechanism to securely erase user data. 3. **Monitoring and Reporting**: Continuously monitor control effectiveness through automated checks and periodic audits. A company using an AI chatbot can aim for a 99.5% compliance rate in data handling protocols, reporting this metric to management to ensure audit readiness and reduce legal exposure.

Taiwanese enterprises face several key challenges with AI compliance: 1. **Extraterritorial Regulations**: Many firms are unaware that regulations like the EU AI Act apply to them if they serve EU customers. The solution is to conduct a gap analysis and form a cross-functional task force. 2. **Talent Shortage**: Experts skilled in AI, data governance, and international law are scarce and expensive. Engaging external consultants and adopting standardized frameworks like ISO/IEC 42001 can bridge this gap. 3. **Weak Data Governance**: Effective AI compliance requires robust data governance, which is often lacking. The solution is to prioritize data governance for high-risk AI applications, starting with a data catalog and lineage tracking to meet transparency and traceability demands.

Winners Consulting specializes in compliance requirements for Taiwan enterprises, delivering compliant management systems within 90 days. Free consultation: https://winners.com.tw/contact