Beyond adoption: unpacking the trust-ethics-decision trade-offs in healthcare AI strategy

Abstract

Purpose This study investigates the organizational mechanisms and management choices through which the strategic implementation of artificial intelligence (AI) reshapes decision-making and professional-technology interaction in healthcare organizations. Design/methodology/approach Adopting an inductive qualitative research methodology, the study analyses in-depth interviews with managers and professionals from healthcare organizations in Portugal. The analysis led to the development of a theoretically grounded model that articulates the mechanisms that facilitate and inhibit the strategic adoption of AI. Findings The results identify four key dimensions and their underlying mechanisms, demonstrating that enhancing efficiency is inherently connected to issues of trust, ethics and the reorganization of decision-making authority. The findings extend the theory by integrating perspectives from socio-technical systems and professional judgment. Practical implications A conceptual framework and propositions are proposed that articulate the link between AI strategy and professional practice. The managerial implications highlight the need for strategic intermediation strategies and organizational readiness for sustainable and viable implementation. Originality/value This research contributes theoretically by refining existing models based on empirical mechanisms and methodologically by justifying the inductive approach to the study of AI management processes, offering insights for the management of healthcare organizations.

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