The adoption of AI technology and an increasingly complex regulatory environment In today's world, where technology advances daily, artificial intelligence (AI) is no longer a future innovation but an essential tool for the present. AI offers greater efficiency and accuracy in business management, excelling in customer service and data analysis. However, the opportunities presented by this remarkable technology are matched by risks that cannot be ignored. From ethical issues and biases arising from flawed data training to legal requirements for regulation, businesses face new challenges. Recent reports from GRC Partners Asia and Bloomberg Law offer notable insights into these issues. GRC Partners Asia, in its report 'How AI Governance in Risk Management Is Reshaping Modern Risk and Compliance' published on April 14, 2026, and Bloomberg Law, in its analysis 'Building Your Company's AI Governance Framework to Reduce Risk' published on April 10, emphasize the growing importance of AI governance in the adoption and utilization of AI technology. AI governance refers to a systematic management framework designed to ensure that AI systems are developed, deployed, and operated responsibly. Specifically, it is a system designed to comply with regulations, support sustainable corporate growth, and simultaneously achieve ethical and public interest goals. The reasons for the importance of AI governance are clear. First, AI technology has a high potential to lead to unintended consequences. In a real-world example, Amazon discovered in 2018 that its AI-powered hiring system systematically gave lower scores to female applicants, exhibiting bias, and subsequently scrapped the program. The U.S. criminal recidivism risk prediction system COMPAS faced controversy following a 2016 ProPublica investigation, which found racial bias, assigning Black defendants twice the recidivism risk score of white defendants. In the financial sector, there have been reported cases where AI loan approval programs in some banks showed prejudice against specific zip code areas or income brackets. Experts point out that these are not mere errors but problems arising from a lack of ethical consideration during the system design phase. Such cases not only damage corporate trust but also carry the risk of leading to legal disputes. Second, the AI regulatory environment is becoming increasingly complex. The European Union (EU) is at the forefront of AI technology regulation with its AI Act, approved in March 2024 and set for full implementation in August 2026. This law classifies AI systems by risk level and requires strict verification processes for technologies categorized as high-risk. Specifically, AI systems in eight areas are classified as high-risk: critical infrastructure, education and vocational training, employment management, access to essential public and private services, law enforcement, border management, and judicial and democratic processes. Failure to comply can result in fines of up to 7% of a company's global annual turnover or 35 million euros, whichever is higher. Such regulations are not confined to overseas examples. South Korea is also actively discussing legal frameworks to establish AI ethics standards and enhance transparency in technology adoption, including the AI Basic Act, which has been pending in the National Assembly since 2023. The Ministry of Science and ICT announced 'AI Ethics Standards' in 2020 and presented a plan for establishing an AI governance system through the 'Strategy for Realizing Trustworthy AI' in 2022. Key Elements and Necessity of an AI Governance Framework Third, AI governance is emerging as a factor that determines a company's reputation and market competitiveness, beyond mere risk management. GRC Partners Asia states in its report, "AI governance not only enables companies to proactively analyze and manage risks but also contributes to gaining the trust of customers and investors through the transparency and reliability it provides." The report particularly emphasizes that AI governance can simultaneously meet regulatory requirements, ethical standards, and organizational goals through four core elements: "establishing accountability, setting clear policies and standards, increasing transparency, and continuous oversight." Bloomberg Law's analysis also stresses the necessity of a systematic framework to effectively manage regulatory, reputational, and operational risks, stating that legal departments play a "critical role in balancing the speed of AI adoption with the management of associated risks." In other words, this has become a strategic management element beyond a mere technical issue. Of course, there are skeptical voices regarding AI governance. Some companies point out that establishing AI governance requires excessive cost and time. Especially for small and medium-sized enterprises (SMEs), there are significant concerns that securing AI-related specialized personnel or applying adv
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