Inteligencia artificial y comunicación corporativa: una evolución estructural analizada desde la bibliometría

Objectives: This study analyzes the development of scientific research on artificial intelligence (AI) applied to corporate communication between 2005 and 2024. The objective is to identify key thematic lines, collaboration dynamics, and institutional concentration patterns, with particular attention to the evolution of academic discourse and its orientation toward sustainability, ethics, and digital literacy. Design/Methodology: A structural bibliometric analysis was conducted based on a corpus of 670 articles retrieved from Web of Science and Scopus. The data were processed using Biblioshiny (Bibliometrix), applying performance analysis, co-authorship networks, keyword co-occurrence, and strategic mapping techniques. This methodology enables the mapping of thematic clusters and the evaluation of the cognitive structure of the field, while acknowledging the inherent limitation of relying exclusively on indexed databases. Findings: Scientific output shows sustained growth since 2016, driven by technologies such as machine learning, natural language processing, and generative systems. Four evolutionary stages were identified, marking a shift from functional approaches to a critical maturity phase centered on ethical governance and institutional responsibility. The most developed areas include communicative automation, algorithmic personalization, and the use of AI in branding and education. Notable imbalances were also found in the geographic and linguistic distribution of knowledge, with a predominance of authors from the Global North and publications in English. Originality/Value: This study offers a novel and replicable systematization of the field, providing a structural perspective on how AI has reconfigured corporate communication from an interdisciplinary standpoint. Its main contribution lies in outlining a research agenda aimed at critically integrating technological innovation, communicative sustainability, and epistemic equity in organizational contexts.