Mapping AI and Public Relations Research: Trends, Theories, and Ethics

Abstract

Artificial intelligence (AI) is reshaping public relations (PR) through automated content production, generative language models, audience segmentation, and data-driven decisionmaking. While scholars highlight AI's potential to enhance efficiency and strategic capability, concerns around transparency, privacy, algorithmic bias, governance, inclusivity, and trust remain central. Despite growing attention, AI-PR research remains unevenly distributed and theoretically fragmented. This study presents a quantitative content analysis of 100 peerreviewed journal articles published between 2016 and 2026, with sustained scholarship emerging from 2018. Guided by three research questions, the study examines publication trends and topical distribution, theoretical frameworks and their integration, and ethical considerations in the literature. Articles were coded for publication year, journal outlet, geographic affiliation, methodological orientation, research design, statistical techniques, sample characteristics, theoretical perspectives, AI tools discussed, and six ethical domains, analyzed using descriptive statistics. Findings indicate rapid growth since 2018, with thematic concentration in AI-mediated persuasion, relationship management, governance, adoption, and organizational transformation. Theoretical diversity exists without consolidation, and ethical engagement is uneven — trust, transparency, bias, and privacy appear frequently, while governance and inclusivity receive limited attention. The literature also remains geographically concentrated in Western academic contexts.