Transformation of the enterprise customer-centricity toolkit under the influence of generative AI development

Abstract

The article investigates the evolution and transformation of the scientific toolkit of enterprise customer-centricity under the conditions of generative artificial intelligence (AI) adoption and domestic market development influenced by overcoming the Soviet legacy. Particular attention is paid to distinguishing between the definitions of "customer orientation" and "customer-centricity" based on the criteria of strategy, culture, technology, and metrics. The former is defined as a tactical service tool, while the latter is conceptualized as a higher management paradigm that rebuilds the business structure around long-term customer value. It is substantiated that the classical concept of the "experience economy" has undergone a significant transformation in Ukraine due to the challenges of martial law, causing a forced transition of domestic business to the human-centric "people for people" (Human-to-Human) paradigm, which is oriented toward satisfying existential needs for security and mutual assistance. A new author's definition of customer-centricity is formulated for the modern Ukrainian market as a management paradigm where the business ecosystem is closely integrated with the human life context under extreme circumstances, the brand acts as a social-empathetic support and a responsible "corporate citizen" that ensures community resilience, and its value is measured by the level of societal support. The technological toolkit based on generative AI is systematized, and its role as an infrastructural driver of empathy is scientifically substantiated, as it automates operational routines and frees up the emotional resources of personnel to resolve crisis situations, thereby creating conditions for deep interaction. The fundamental shift from reactive customer experience to cognitive and agentic AI is characterized, involving a transition from passive systems of record to autonomous assistants capable of recognizing emotions and acting proactively. The idea regarding the risks of an "empathy debt" under conditions of over-automation is formulated, and the feasibility of implementing a hybrid human-machine model is scientifically substantiated. It is proven that the hybrid "human + AI" format ensures speed and scale, while the human provides genuine empathy.