WHO SHAPES EMPLOYEES’ ATTITUDES TOWARD AI? A CROSS-SECTIONAL STUDY OF ORGANIZATIONAL TRUST IN THE PUBLIC SECTOR
Abstract
Attitudes towards AI are part of the cognitive dimension of initial trust in AI. While the literature generally focuses on individuals' trust tendencies and cognitive-emotional characteristics, it largely neglects the influence of the organizational context. This study investigates whether initial trust in AI is shaped not only by individual factors but also by trust in the organization, the manager, and colleagues. In this quantitative study conducted with 196 participants in the public sector, the Organizational Trust Scale (α = .902; explained variance = 64.41%; KMO = .880) and the Artificial Intelligence Attitude Scale (α = .878; explained variance = 69.45%; KMO = .866) were used. The Shapiro-Wilk test determined that the data were not normally distributed, and Spearman correlation analyses were applied. The findings show no significant relationship between overall organizational trust and general attitudes toward AI (r = .096; p = .182), positive attitudes (r = .082; p = .255), and negative attitudes (r = .086; p = .230). Similarly, trust in colleagues is not statistically significant in relation to positive (r = .063; p = .383) and negative attitudes toward AI (r = -.134; p = .062). In contrast, trust in the manager shows a weak but significant relationship with positive attitudes (r = .144; p = .045) and a stronger and more significant relationship with negative attitudes (r = .281; p < .001). Furthermore, a strong and significant relationship was found between trust in the organization and negative attitudes toward AI (r = .318; p < .001). These findings indicate that organizational trust does not directly and unidirectional shape attitudes toward artificial intelligence. This suggests that AI may be perceived primarily as a managerial and institutional decision domain, where trust relates not only to acceptance but also to heightened risk awareness.
Keywords
References
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Details
Primary Language
English
Subjects
Technology Management, Public Sector Organisation and Management, Organizasyon, Strategy, Management and Organisational Behaviour (Other)
Journal Section
Research Article
Authors
Publication Date
June 18, 2026
Submission Date
October 8, 2025
Acceptance Date
March 2, 2026
Published in Issue
Year 2026 Number: 100