<![CDATA[Artificial Intelligence (AI) has emerged as a transformative tool in Human Resource Management (HRM), particularly in employee age verification for legal compliance and workforce planning. Verifying employee age is crucial in ensuring adherence to labor regulations that prohibit child labor and enforce age-related employment restrictions, especially in high-risk industries such as construction and manufacturing. This study explores how AI-based dental radiographic analysis can be integrated into HRM to provide a more objective, accurate, and fraud-resistant alternative to conventional identity verification methods. The research examines various AI techniques, including deep learning models such as ResNet, VGG16, and EfficientNet, and machine learning approaches like Random Forest and Support Vector Machines, which enhance classification accuracy in age estimation. While AI has demonstrated high efficiency in forensic and medical applications, its adaptation to HRM requires addressing critical challenges, including data privacy concerns, regulatory acceptance, and cost-effectiveness. Additionally, integrating AI into HRM demands a framework that aligns with labor laws and ethical considerations to ensure compliance and minimize potential biases in AI-based decision-making. This study suggests that AI-driven age verification can improve recruitment accuracy, support legal workforce management, and reduce risks associated with underage employment. Future research should focus on the economic feasibility of AI implementation in HRM, sector-specific case studies, and regulatory frameworks that facilitate AI adoption in labor compliance.]]>
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