The Integration of Artificial Intelligence in Local Media Journalism: Perceptions of Quality, Credibility, and Ethical Governance among Greek Media Professionals

Abstract

The increasing integration of artificial intelligence into journalism has generated significant scholarly attention regarding its implications for content quality, editorial credibility, and professional ethics. However, limited empirical research has examined how journalists in small-scale, resource-constrained local media environments perceive and operationalize AI tools within their professional workflows. This study addresses that gap by investigating the perceptions of Greek local media professionals regarding AI integration in journalistic practice. Through a mixed-methods design combining semi-structured interviews and structured attitudinal measurement, data were collected from eighteen media professionals, including journalists, editors, and media technologists, working in Greek local media organizations. Thematic analysis of qualitative data revealed three principal dimensions of AI integration: operational efficiency in routine tasks, analytical enhancement in investigative reporting, and persistent normative concerns regarding algorithmic bias, transparency, and professional skill erosion. Descriptive statistical analysis of a composite attitudinal index indicated a moderately positive but cautious orientation toward AI adoption (M = 3.9, SD = 0.64). Findings further demonstrate that AI adoption in Greek local media remains predominantly experimental and individually driven rather than institutionally embedded. The study contributes to an underrepresented empirical context in AI-journalism scholarship and proposes a tripartite framework encompassing operational, analytical, and normative dimensions for understanding AI integration in local newsrooms. Recommendations are offered for structured AI governance, professional training, and curricular reform in media education.