Generative AI algorithms in regional media: visual content creation practices.
DOI:
https://doi.org/10.47475/2070-0695-2026-60-2-133-140Keywords:
AI content, AI visualization, artificial intelligence technologies, regional media, media practicesAbstract
The article describes the established practices of using generative artificial intelligence technologies to create visual content in regional media operating under conditions of resource constraints and lack of institutional support. The purpose of the work is to systematize approaches to the use of generative algorithms in a specific media practice of the Altai regional information agency "Amitel". The choice of this media as an object of research is due to its representativeness for the regional media system, as well as the presence of a systematic practice of using generative artificial intelligence technologies in the creation of visual content. The research methodology is based on content analysis, during which it was possible to identify the categorization of publications with AI visualization, the types of neural network models involved, and the features of image labeling. The empirical base consisted of a corpus of 21,600 materials published on the Amitel News Agency website from January to December 2025. As a result of the research, it has been established that the use of AI algorithms is moving from experimental practices to the beginning of the formation of a sustainable system for using innovation. The thematic differentiation of the use of generative technologies has been revealed, where neural networks are used to visualize abstract concepts and events that do not have photographic confirmation. There are also identified topics where the use of AI mechanisms is not fixed and media producers still prefer traditional ways of illustrating. The main conclusions of the study capture the formation of a sustainable regional media practice for integrating AI solutions based on the principles of pragmatic selectivity and openness. Regional media adapts innovations through the selection of those tools that solve specific production tasks, rejecting the use of technology where traditional methods remain more effective, and ensuring transparency of the origin of content for the audience.
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