High-Risk AI

High-Risk AI is a legal and regulatory concept primarily established by the European Union's AI Act. It defines AI systems that, due to their intended purpose, pose a high risk to the health, safety, or fundamental rights of individuals if they malfunction or provide inaccurate outputs. Annex III of the EU AI Act explicitly lists high-risk use cases, such as AI in critical infrastructure, educational assessment, employment (e.g., CV-sorting), and credit scoring. In a risk management context, these systems are subject to mandatory ex-ante conformity assessments, distinguishing them from 'unacceptable risk' AI (which is banned) and 'low/minimal risk' AI (which has transparency obligations). Enterprises deploying high-risk AI must adhere to strict obligations, including implementing a risk management system as outlined in Article 9 of the Act, ensuring data quality, maintaining technical documentation, and registering the system in an EU database, aligning with frameworks like ISO/IEC 42001.

Enterprises must implement a structured risk management process for high-risk AI. The first step is identification and classification, where a company systematically screens its AI systems against the criteria in Annex III of the EU AI Act to determine their risk level. For example, an AI used for credit scoring falls under this category. The second step is conducting a mandatory conformity assessment before market deployment. This involves establishing a robust risk management system, ensuring high-quality and unbiased training data, creating comprehensive technical documentation, and implementing human oversight mechanisms, as required by the Act. The final step is continuous post-market monitoring to track real-world performance, report serious incidents to authorities, and apply corrective actions. A global bank, for instance, applied this framework to its loan-approval AI, achieving a 100% audit pass rate and reducing biased decision appeals by 25%.

Taiwanese enterprises face three key challenges. First, the extraterritorial scope of the EU AI Act creates a compliance gap, as many firms exporting to the EU are unfamiliar with its stringent requirements, while Taiwan's domestic AI legislation is still developing. Second, small and medium-sized enterprises (SMEs) often lack the financial resources and specialized talent (e.g., AI ethicists, legal experts) to implement the required complex risk management and documentation processes. Third, many companies have immature data governance frameworks, making it difficult to meet the Act's strict requirements for high-quality, unbiased training data. To overcome this, firms should prioritize conducting a regulatory gap analysis with expert help, adopt international frameworks like the NIST AI RMF to structure their efforts, and invest in a robust data governance program, starting with products intended for the EU market.

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