Governments increasingly communicate with their publics through artificial intelligence (AI), yet media and communication scholarship has concentrated on newsrooms and platforms, leaving the algorithmically mediated communication of the state under-theorised. This study asks how a state institutionally constructs, coordinates, and accounts for AI-enabled strategic communication, defined here as the intentional, institutionally coordinated use of AI systems by government entities to inform, persuade, listen to, and build relationships with publics. It develops the AGORA framework—Architecture, Generation, Orchestration, Responsiveness, Accountability—which conceptualises the state’s AI-mediated communication system as an algorithmic public square and derives six propositions offered as theoretical expectations for subsequent testing rather than as relationships tested here. A six-phase reflexive thematic analysis, following a documented search and screening protocol, was applied to a corpus of 34 United Arab Emirates (UAE) and comparative documents (2017–2026). Every quantitative indicator was then classified on a five-tier provenance ledger distinguishing binding law, policy target, officially reported performance, independently produced benchmark, and untraceable claim. Four themes emerge: a layered governance architecture in which the communicative safeguards rest on strategy and non-binding ethical guidance because the federal data-protection statute excludes governmental entities from its scope; documented algorithmic communication mechanisms; officially reported sectoral performance and its provenance; and contextual benchmarking against Singapore and Republic of Korea. The findings show the UAE state operating as a front-stage communicative actor whose agenda construction, personalisation and responsiveness are computationally augmented and specify where institutional claims outrun independent verification. Because the design is documentary, public engagement, trust, and sustainable development outcomes are positioned as expected outcomes outside the framework and are not empirically demonstrated. This study contributes a transferable framework, a four-stage maturity trajectory, and a provenance protocol for research on AI-mediated government communication.
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Abdallah et al. (2026) studied this question.
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