ARTIFICIAL INTELLIGENCE IN THE PROJECT MANAGEMENT SYSTEM FOR DIGITALIZATION OF MILITARY MARKETING: PSYCHOLOGICAL MECHANISMS OF ADVERTISING INFLUENCE

Abstrakt

INTRODUCTION. Under the conditions of communication digitalization and growing competition for human resources, military marketing increasingly requires project-managed approaches to the planning, personalization, and optimization of recruitment messages. Artificial intelligence serves as a tool for automated audience segmentation, prediction of behavioral responses, adaptation of creative content, and improvement of the effectiveness of digital campaigns. At the same time, the use of algorithmic technologies intensifies the risks of distrust, advertising avoidance, cognitive overload, and privacy concerns. This makes it necessary to provide a scientific substantiation of a model that integrates artificial intelligence tools, digitalization project management, and psychological mechanisms of advertising influence within the system of military recruitment.

RESEARCH HYPOTHESIS. The hypothesis consists in substantiating that the effectiveness of digital recruitment communications in military marketing increases when artificial intelligence is integrated into the project management system while simultaneously ensuring control over psychological indicators of trust, transparency of AI involvement, authenticity, cognitive load, and the risk of advertising avoidance.

PURPOSE. To identify the patterns of integrating artificial intelligence tools into the project-based framework of planning, monitoring, and optimization of digital recruitment communications in military marketing by operationalizing psychological mechanisms of advertising influence in the form of measurable indicators of effectiveness, trust, and advertising avoidance.

METHODS. Content analysis of publicly available digital recruitment messages; purposive bibliographic selection of scientific sources; comparison; abstraction; synthesis; operationalization of psychological constructs on a 0–100 scale; mathematical modeling; descriptive statistics; regression-based calibration of weights for integrated indicators; interpretive analysis.

CONCLUSIONS. In the context of military marketing digitalization, artificial intelligence not only enables the scaling and personalization of recruitment messages but also requires systematic project-based control over the psychological consequences of advertising influence. The proposed model makes it possible to integrate AI tools with indicators of trust, transparency, authenticity, cognitive load, social media fatigue, and privacy-related risks. The feasibility of using three integrated indicators has been substantiated: AIPCS for assessing the predicted potential of recruitment effectiveness, AAP for determining the algorithmic potential for advertising avoidance, and APGI for evaluating the quality of managerial configuration of AI-assisted advertising communications. The practical value lies in the possibility of applying these indicators at control points within digitalization projects in military recruitment.

KEYWORDS: military marketing; artificial intelligence; project digitalization management; digitalization; recruitment communications; advertising psychology; advertising influence; trust; cognitive load; advertising avoidance.