When the Political-Administrative Chain Looks Away: Exploring Swiss Cantonal Workforce Perceptions of AI-Driven HR Analytics Implementation

The deployment of AI-driven HR analytics in public administration promises to enhance evidence-based decision-making and organizational effectiveness. Yet adoption in Swiss public sector organizations remains overwhelmingly descriptive, with predictive and prescriptive capabilities significantly underutilized. While a growing body of research examines technical and organizational barriers to HR analytics maturity, comparatively little attention has been paid to how public sector employees anticipate these tools and to how political-administrative chains shape whether workforce evidence becomes actionable. Drawing on twenty semi-structured interviews conducted in a French-speaking Swiss cantonal administration, this study documents the anticipatory perceptions of employees and managers, and reads them through HR attribution theory, HRM system strength theory, and the concept of strategic ignorance. Participants express a conditional openness to AI-driven analytics that differs sharply between recruitment and evaluation use cases, describe a pre-existing political-administrative pattern in which workforce evidence is produced, circulated, and ultimately absorbed without consequence, and anticipate that AI-driven tools would be incorporated into that pattern rather than disrupt it. The findings identify a barrier qualitatively distinct from technical and competency-based obstacles. Successful adoption in politically accountable public administrations requires not only technical readiness and data literacy but also politico-administrative courage.