Abstract
Introduction. The spread of artificial intelligence in the publishing industry is transforming not only individual production operations but also professional roles, editorial procedures, management models, content quality criteria, and approaches to organizational governance. Under these conditions, AI should be considered not only as a technological tool but also as a factor of institutional change in the professional environment.
Relevance and purpose. The relevance of the study stems from the insufficient conceptualization of the organizational dimension of AI implementation in Ukraine’s publishing industry. The article aims to identify the specific features of AI institutionalization by analyzing the relationship between individual professional use of the technology and the level of its organizational implementation.
Methodology. The empirical basis is a quantitative survey conducted from December 2025 to February 2026 with 374 respondents. Valid-response subsamples were used for particular analytical blocks, while a matched subsample of n = 240 was used to compare individual AI use with respondent-reported organizational AI implementation. The analysis employed descriptive statistics, the chi-square test, and the two-sided McNemar test.
Results. AI institutionalization was found to be uneven and predominantly transitional. Some form of official AI implementation in their organization was reported by 61.3% of respondents, with localized use being the most common format. Within the matched subsample, active professional AI use at the individual level was recorded among 77.1% of respondents. The study revealed a low level of formalization of AI practices, weak internal policies and contractual regulation, the predominance of self-education, and insufficient professional training as the most frequently reported barrier to implementation.
Conclusions. The findings indicate that AI is already widely used at the individual level within the analyzed publishing environment, while respondent-reported organizational AI implementation remains uneven and incompletely formalized. The novelty of the study lies in identifying the asymmetry between individual use and respondent-reported organizational implementation of AI. The findings may inform the development of internal policies, training programs, mechanisms for responsible AI use, and managerial coordination.
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