THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE PERSONALIZATION OF EVP (EMPLOYEE VALUE PROPOSITION) IN MODERN BRAND STRATEGIES

Abstract

The article provides a comprehensive theoretical substantiation and develops a sophisticated conceptual model for integrating Artificial Intelligence technologies into employer branding strategies. The primary goal is to facilitate the transformation of a traditional, static EVP into a dynamic, hyper-personalized interaction system. Within the context of the global labor market’s radical transformation observed between 2024 and 2026, the study identifies that conventional «one size fits all» approaches have lost their strategic efficacy. This decline is driven by the increasing differentiation of employee expectations across diverse demographic groups, specifically Gen Z and Gen Alpha, who prioritize digital well-being, mental health support, and professional autonomy. The research highlights a fundamental paradigm shift from a «static package» of material benefits toward a «Dynamic Human Experience». This new model is built upon three technological pillars: real-time sentiment analysis using Natural Language Processing to monitor corporate climate; generative AI models for creating tailored candidate content; and sophisticated recommendation algorithms that power «Benefit Cafeterias» The author conceptualizes the mechanism of EVP evolution through machine learning, enabling a shift from macro-segmentation to micro-segmentation based on the analysis of complex digital footprints and behavioral patterns. A significant contribution of this work is the 4-step algorithm for continuous EVP management, which ensures that the brand’s value proposition evolves synchronously with the individual employee’s journey-from predictive attraction and adaptive onboarding to AI-driven retention and alumni-friendly separation strategies. Furthermore, the scientific novelty is enhanced by the definition of a specific set of KPIs designed to measure emotional connectivity within automated digital channels. These metrics include the Sentiment Score, Humanization Rate, and the AI Trust Index, providing a framework to monitor the «humanity» of the digital ecosystem. The article concludes by addressing the critical «ethical paradox» of algorithmic branding, proposing a «Human-in-the-loop» strategy to mitigate risks of dehumanization, algorithmic bias, and privacy concerns, thereby ensuring the long-term sustainability and inclusivity of the employer brand.