Law of Obligations

The Law of Obligations, originating from Roman law, is a cornerstone of civil law systems. It governs the rights and duties between parties (a creditor and a debtor). These obligations arise primarily from contracts, torts (wrongful acts), unjust enrichment, or management of another's affairs without a mandate. In risk management, it underpins contractual and liability risks. For instance, the EU AI Act imposes new statutory obligations on AI providers, such as transparency and human oversight for high-risk systems. A breach of these duties can trigger tortious liability, a concept rooted in the Law of Obligations. This is analogous to GDPR Article 82, which establishes the right to compensation for data breaches, applying principles of tort law to data protection and holding controllers or processors liable for damages.

Applying the Law of Obligations in enterprise risk management involves three key steps. Step 1: Obligation Identification. Systematically map all contractual duties with customers and suppliers, alongside statutory obligations from regulations like the EU AI Act, to create a comprehensive 'obligation register.' Step 2: Risk Assessment and Control. Evaluate the likelihood and impact of breaching each obligation and design controls, such as embedding clear liability and indemnity clauses in supplier contracts for AI systems. Step 3: Monitoring and Response. Implement continuous monitoring of regulatory changes and establish an incident response plan for breaches. For example, a Taiwanese AI firm entering the EU market updated its service contracts to align with the AI Act's transparency requirements, achieving a 99% compliance audit pass rate and reducing potential contractual disputes by an estimated 30%.

Taiwanese enterprises face three main challenges. First, Regulatory Complexity: Keeping pace with extraterritorial laws like the EU AI Act is difficult for SMEs with limited legal resources. Second, Supply Chain Liability: Assigning fault is complex when an AI failure results from multiple third-party components (e.g., APIs, models), creating ambiguous liability. Third, Intangible Damages: Quantifying and proving damages from AI-driven discrimination or reputational harm is challenging under existing legal frameworks. To overcome this, firms should first establish a cross-functional AI governance task force (3-month priority). Next, they must enforce stricter supplier due diligence, demanding contractual clarity on liability (6-month priority). Finally, they should explore specialized AI liability insurance to transfer residual risks.

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