Abstract: Personnel evaluation systems are undergoing fundamental transformation as organizations confront the limitations of traditional appraisal methods in increasingly dynamic, digitized, and data-rich work environments. Building upon Ilich's (2026) Integrated Personnel Evaluation Model (IPEM), this article examines how conventional performance management approaches—characterized by episodic reviews, supervisor-driven ratings, and structural biases—are systematically misaligned with contemporary organizational realities. Through integrative analysis of recent scholarship on HR analytics, artificial intelligence in human resource management, and psychological safety research, this study explores how the IPEM framework addresses three persistent tensions in modern evaluation practice: the conflict between algorithmic objectivity and relational legitimacy, the trade-off between continuous data capture and employee trust, and the contradiction between evaluation as control versus evaluation as development. Findings demonstrate that effective contemporary evaluation systems must be simultaneously more data-informed and more human-centered, integrating analytical precision with developmental purpose. This analysis contributes a theoretically grounded and practically actionable perspective for organizations seeking to build valid, trusted, and strategically relevant personnel evaluation capabilities in the digital economy.
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