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Purpose Artificial intelligence (AI) is fueling a tsunami of change in business. Today, managers can deploy AI decision support solutions to remain globally competitive. This transformation on all aspects of business demands deeper inquiry into the human interaction with AI technology given the relevant ethical considerations. The purpose of this paper is to review existing measurement scales and propose a holistic framework and associate psychometrics that will guide future knowledge development. Design/methodology/approach Qualitatively, the authors conduct a literature review and examine the studies that validated trust measurement scales. Quantitatively, this study provides a holistic examination of all relevant AI trust scales and uses them into a single survey across two phases of business practitioners to tease out a multitude of AI trust dimensions through factor analysis. Findings Scholars who purport to be measuring AI trust are often not. To guide knowledge creation, this paper proposes a general framework of AI trust encompassing six distinct dimensions in a single second order construct. Moreover, the authors provide a holistic 20-item scale for academicians to employ for theory advancement. Originality/value By analyzing survey data from professionals who use AI in their work, this study offers one of the most holistic examinations of AI trust to date. The resulting framework and 20-item scale provide a robust instrument for diagnosing, understanding and fostering trust in AI, thereby supporting more effective human–AI collaboration and AI-driven knowledge management.
Dickens et al. (Tue,) studied this question.