GENERATIVE ENGINE OPTIMIZATION (GEO): A NEW PARADIGM OF DIGITAL VISIBILITY IN THE AGE OF AI-POWERED SEARCH

This article examines the concept of Generative Engine Optimization (GEO) in the context of the
transformations enabled by the integration of generative artificial intelligence into contemporary information search
and retrieval practices. The aim of the paper is to clarify the conceptual standing of GEO in connection with Search
Engine Optimization (SEO) and to explore its consequences for digital marketing strategy. Methodologically, the study
adopts an integrative review approach, combining selective analysis of emerging literature with the integration of
established theoretical frameworks, in order to build a coherent interpretative framework for a field still in the
conceptualization phase. The analysis suggests that GEO does not replace SEO, but introduces a complementary logic
of digital visibility, in which the main stake is no longer exclusively positioning in the results pages, but the probability
that a brand, a source, or a content will be taken up, mentioned, or cited in the responses generated by platforms based
on large-scale linguistic models. The article discusses GEO theoretically in relation to the diffusion of innovations
theory, the technology acceptance model, and the consumer-based brand equity perspective. In terms of application,
the implications for content production, informational authority, performance measurement, and the ethical dimension
of optimization practices are highlighted. The paper also highlights the main limitations of the field: algorithmic
opacity, lack of standardized evaluation methods, and the incipient nature of academic validation. Finally, useful
research directions are proposed to consolidate GEO as a relevant topic in the marketing literature.