ARTIFICIAL INTELLIGENCE IN STRATEGIC COMMUNICATION: EMERGING CHALLENGES FOR MEDIA REGULATION AND DEFAMATION JURISPRUDENCE

Abstract

The rapid integration of Artificial Intelligence (AI) into strategic communication has transformed the production, dissemination, and amplification of institutional messaging. AI-driven systems now perform automated content generation, predictive analytics, audience segmentation, and real-time reputation management with minimal human intervention. While these technologies enhance efficiency and strategic precision, they simultaneously disrupt foundational principles of media regulation and defamation jurisprudence. Traditional legal frameworks governing speech are predicated upon identifiable human authorship, editorial control, and fault-based liability. Algorithmic communication, however, introduces autonomous or semi-autonomous content generation processes that complicate attribution, intent, and accountability. This study critically examines the regulatory and doctrinal tensions arising from AI-mediated communication within corporate and institutional contexts. It interrogates whether existing media laws designed for print, broadcast, and later digital platforms are equipped to address algorithmic publication and amplification. Particular attention is devoted to defamation law, where elements such as publication, falsity, fault, and reputational harm must be reassessed in light of machine-generated outputs. Through doctrinal analysis, comparative evaluation, and empirical inquiry into AI adoption in strategic communication, the research identifies significant accountability gaps and proposes a recalibrated liability framework emphasizing institutional responsibility, transparency obligations, and enhanced due diligence standards. The study contributes to evolving debates on media governance, corporate accountability, and the preservation of reputational dignity within algorithmically mediated public discourse.