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This article demonstrates a methodology for aligning employee skills with company goals during digital transformation, suggesting a practical solution for HRM challenges.
This article presents a structured, competency-based methodology for aligning employees’ skills with the company’s strategic goals during digital transformation. The approach addresses key challenges in AI-driven Human Resource Management (HRM), such as complexity, transparency, and regulatory compliance (e.g., EU AI Act). Utilizing a self-organized learning neural network, the Self-Enforcing Network (SEN), the methodology enables systematic assessment and visualization of individual and team competencies, supporting objective, data-based HR decisions. The methodology was designed by a real-world application and demonstrates how it can support team composition, highlight skill gaps and facilitate strategic alingment. The developed model remains adaptable to differnet organizations and organizational contexts offering a robust, reproducible solution for navigating the complexities of AI adoption in HRM while meeting the highest standards of ethical and regulatory integrity.
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Dutzi et al. (2026) studied this question.
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