Introduction of Artificial Intelligence into Organizational Practices: Trust, Legitimacy and Ethical Challenges (Based on Expert Interviews)

Abstract

The article examines how professionals from diverse occupational contexts — banking, IT, academia, business analytics, and small entrepreneurship — construct trust in artificial intelligence (AI), interpret its institutional legitimacy, and articulate ethical boundaries of automation in organizational practices. The empirical basis includes six semi-structured expert interviews conducted in 2026, with a structured author-developed guide of eight thematic blocks; the qualitative material is contextualized by author's survey data (n = 448, Saint Petersburg, 2024–2026) and by all-Russian polling data from VCIOM, Levada Center, and HSE. The research design is framed as an exploratory qualitative study with quantitative validation: interviews reconstruct experts' meaning constructs, while the survey captures the prevalence of corresponding attitudes in a broader population. Transcripts were analyzed using thematic analysis in the Braun & Clarke tradition. Three profiles of expert attitudes toward AI are identified — operational, techno-critical, and entrepreneurially-adaptive; a stable normative position of “trust but verify” emerges across professional contexts; a regulatory gap is documented between strong public demand for state oversight of AI (80%) and very low awareness of existing legal norms (16%). The article contributes to the journal's methodological debate on qualitative approaches to studying AI and proposes the framework of “exploratory qualitative research with quantitative validation” as a practical alternative to strict mixed-methods designs in limited-sample research situations.