Governing artificial intelligence in strategic communication: institutional enablement and communication effectiveness in digitally mediated environments

Abstract

Artificial intelligence is increasingly embedded in strategic communication infrastructures, yet limited empirical research has examined the institutional conditions under which AI contributes to communication effectiveness. This study develops and tests a socio-technical, governance-centered model examining how AI professional competency, organizational AI support, perceived value of AI and perceived AI-related risk relate to communication effectiveness among public relations professionals in the United Arab Emirates. A cross-sectional quantitative survey was conducted among 234 public relations and communication professionals in the UAE. The study employed validated multi-item measures to assess AI professional competency, organizational AI support, perceived value of AI, perceived AI-related risk, and communication effectiveness. Data were analyzed using descriptive statistics, independent-samples t-tests, one-way ANOVA, Pearson correlation, hierarchical multiple regression and reliability analysis. Organizational AI support emerged as the only significant predictor of communication effectiveness, explaining substantial variance beyond organizational controls. AI professional competency, perceived value of AI and perceived AI-related risk did not exert independent effects in the regression model. No significant differences were found across AI training exposure or organizational sectors. The findings demonstrate that governance structures, leadership commitment, and institutional readiness are more influential than individual competencies or technology perceptions in explaining AI-enabled communication effectiveness. The study is limited to a cross-sectional survey of communication professionals in the UAE and therefore cannot establish causal relationships or be generalized to all national contexts. The reliance on self-reported perceptions may also introduce response bias. Future research should employ longitudinal and cross-national designs and incorporate objective organizational performance measures to further examine how governance frameworks influence AI-enabled communication effectiveness. The findings suggest that organizations seeking to enhance communication effectiveness through AI should prioritize institutional enablement over technology acquisition alone. Leadership commitment, governance frameworks, organizational support and ethical oversight appear more critical than individual AI competency in translating technological capabilities into communication performance. The study offers practical guidance for communication leaders developing AI governance strategies within digitally mediated organizational environments. Effective AI integration in strategic communication requires governance structures that promote transparency, accountability, and responsible organizational use. Strengthening institutional support for AI can improve communication quality while helping organizations address ethical challenges, misinformation risks, and stakeholder trust in digitally mediated environments. These findings contribute to broader discussions on responsible AI adoption in communication practice. This study advances strategic communication scholarship by conceptualizing AI as a governance-conditioned communicative capability rather than merely a technological resource. Drawing on a socio-technical systems perspective, it demonstrates that institutional enablement – rather than professional competency or perceived technological value – is the principal mechanism linking AI integration to communication effectiveness. The study extends digital corporate communication research by providing empirical evidence from the UAE and offering a governance-centered explanation of AI-enabled communication performance.