Abstract: Problem. The increasing integration of Generative Artificial Intelligence into marketing activities poses a theoretical challenge concerning its role within marketing management systems. Existing studies predominantly examine Generative Artificial Intelligence as a discrete analytical device, while limited attention has been devoted to its function as an embedded operational infrastructure shaping organizational capabilities and efficiency. Methodology. A conceptual systematic literature review was conducted on peer-reviewed publications indexed in the Web of Science, Scopus, and Russian Science Citation Index databases for the period 2015–2025. Following predefined selection criteria, 87 publications were included in the analysis. Thematic synthesis was performed using NVivo 14 software, and coding reliability was verified by two independent coders, resulting in Cohen's kappa coefficient of 0.84. The analysis was informed by the theoretical perspectives of the Resource-Based View, Dynamic Capabilities, Market Orientation, Marketing Agility, and Systemic Economics. Research Results. A theoretical framework is developed that reconceptualizes Generative Artificial Intelligence as an infrastructural component of marketing management rather than a standalone technological instrument. Five dimensions of emergent efficiency are identified: Structural Adaptability, Process Elasticity, Temporal Compression, Reliability Stabilization, and Scalable Orchestration. The concept of infrastructural operant capital was proposed as an extension of the Resource-Based View, and dynamic capabilities were reframed as infrastructure-embedded organizational properties. Practical Application. The proposed framework may be applied to the design and management of artificial-intelligence-enabled marketing systems. Practical implications include support for strategic resource allocation, capability development, organizational design, performance measurement, risk management, and talent development, thereby facilitating the effective integration of Generative Artificial Intelligence into contemporary marketing management practices.

Keywords: generative artificial intelligence, strategic marketing management, dynamic capabilities, marketing agility, infrastructural operant capital, market orientation, systematic literature review, emergent efficiency, marketing infrastructure

For citation: Eissa, A. M. A. A. (2026). Generative artificial intelligence as infrastructure of marketing operational efficiency: a five-dimensional framework for emergent efficiency. Scientific Journal "Manager", 3(117), 102-112. EDN: OZUZDY.

Information about the author: A. M. A. A. Eissa - PhD student at the UrFU.