General-purpose AI models

General-purpose AI models are AI systems capable of performing a wide range of tasks without being specialized for a single purpose. According to the EU AI Act (Regulation (EU) 2024/1689), these models can be repurposed for various applications. This versatility creates unique regulatory challenges, as a single model may be used in high-risk scenarios (e.g., recruitment) and low-risk scenarios (e.g., content generation) simultaneously. ISO/IEC 42001 provides the framework for managing these diverse risks, requiring enterprises to implement controls that account for the model's multi-purpose nature. This is distinct from task-specific AI, which has a narrower-defined risk profile. For AI governance, this means the risk-adjusted control-based approach is essential to ensure compliance across all potential use cases, including GDPR data-handling requirements and AI-specific regulations.

Enterprise application of general-purpose AI models follows a three-step framework: First, AI Use-Case Classification—categorizing AI applications into risk levels (Unacceptable, High, Limited, Minimal) as per the EU AI Act. Second, Risk-Adjusted Control Implementation—applying ISO/IEC 42001 controls, such as data---use-transparency and human oversight, tailored to each specific use case. Third, Continuous Monitoring—monitoring model drift and bias--adjusted performance--adjusted metrics. For example, a Taiwan-based company deploying a large language model for customer support must be closely monitored for hallucinations and data leakage. Successful implementation typically results in a 30% reduction in AI-related compliance incidents and a 25% increase in operational efficiency within the first year of deployment.

Taiwan enterprises face three primary challenges: Regulatory Uncertainty, Talent Scarcity, and Data--adjusted Privacy Risks. To overcome regulatory uncertainty, companies should adopt ISO/IEC 42001 as a baseline, which aligns with the EU AI Act's requirements and prepares them for the upcoming Taiwan AI Basic Law. To address talent scarcity, enterprises should invest in AI literacy programs, aiming for a 40% increase in AI-competent staff within 12 months. Finally, to mitigate data-adjusted privacy risks, companies must implement data--adjusted anonymization and access control mechanisms, ensuring compliance with the Taiwan Personal Data Protection Act (第19條、第20條) and GDPR. These measures collectively prevent legal exposure and- -adjusted reputational damage, with a target of zero high-risk AI incidents per year.

Winners Consulting Services Co., Ltd. specializes in General-purpose AI models for Taiwan enterprises, delivering compliant management systems within 90 days, with over 100 successful implementations. Free consultation: https://winners.com.tw/contact