Adapting Marketing to the New Architecture of Digital Presence in the Era of Generative AI

The article aims to investigate the transformation of digital presence architecture under the growing influence of generative artificial intelligence (GenAI) and to develop a basis for adapting marketing strategies in algorithmically mediated environments. Analysis results. The study introduces the concept of digital presence as a dynamic architecture composed of five interdependent components: owned media, social media, earned/shared media, paid media, and the AI-generated content environment. These elements no longer function as discrete channels but as nodes within a real-time, algorithm-driven ecosystem. GenAI transforms the logic of digital presence from deliberate messaging to context-aware synthesis, whereby brand narratives are assembled probabilistically and conversationally based on prior data, user intent, and semantic structure. A key finding of the study is that generative AI, particularly through large language models (LLMs), alters the content discovery process by repositioning itself as the user’s primary interface with the digital environment. This change undermines the efficacy of traditional search and advertising strategies and demands a new paradigm centered on algorithmic compatibility. In this context, the research describes Generative Engine Optimization (GEO) – a strategy aimed at increasing a brand’s algorithmic visibility through semantically structured and machine-readable content. Unlike traditional SEO, GEO focuses on enhancing the likelihood of being included in synthesized AI outputs, often without explicit attribution. The study further reveals that visibility in GenAI environments is contingent upon the brand’s ability to provide content that aligns with the interpretive logic of LLMs. This includes adopting a modular content architecture, using domain-relevant terminology, maintaining tone neutrality, and ensuring semantic coherence. The distinction between digital identity – the intended representation curated by the organization and digital brand image – the perception constructed through AI responses and user interactions – is particularly emphasized. The discrepancy between these two layers can critically affect brand recognition in AI-mediated environments, making the coherence of both human- and machine-facing representations a core strategic issue. The research also outlines the role of AI-generated content as a new layer of communication infrastructure. Generative models often act as intermediaries between users and brands, filtering, restructuring, or even replacing original messaging with system-generated interpretations. As such, digital presence becomes a co-constructed outcome of algorithmic aggregation, user interaction, and the strategic positioning of content across data ecosystems. The study incorporates recent empirical data showing changes in click-through behavior, declining effectiveness of paid ads, and rising user reliance on generative tools such as ChatGPT or Gemini for decision-making. These dynamics reinforce the conclusion that brand communication must now function within a hybrid regime of human and artificial interpretation.