Optimization of influencer marketing processes using artificial intelligence

the purpose of this study is to justify modern trends in improving efficiency and optimizing influencer marketing processes using advanced AI technologies. Methods: analysis of scientific sources, a literature review, as well as visualization methods (graphical and tabular analysis). Findings: The study proposes a conceptual theoretical model of influencer marketing, reflecting the standardized stages of preparing and conducting advertising campaigns with opinion leaders. Based on this model, pathways and directions for optimizing influencer marketing processes using AI technologies are substantiated. The study examines tools for automated influencer selection, personalized targeting, campaign performance forecasting, content generation, and more. General ideas about the impact of AI on the effectiveness of marketing strategies when working with influencers are presented. Conclusions: the proposed approach to influencer marketing, combined with the prospects and advantages of integrating AI into its processes, allows companies to comprehensively address typical tasks of selecting opinion leaders and managing content, improve forecasting accuracy, and reduce costs—both financial and time-related. The study contributes to the development of marketing communications in a dynamic digital environment.

influencer marketing, artificial intelligence, optimization, marketing communications, targeting, forecasting, personalization, automation, content generation, AI technologies, AI, theoretical foundations of influencer marketing