From AI Enthusiasm to Accountable HR: Building the Conditions for Responsible Adoption

Abstract: Artificial intelligence adoption in human resource management requires more than capable technology and optimistic users. It requires organizational arrangements that make consequential decisions understandable, contestable, and accountable. Building on Poo-Udom’s (2026) mixed-methods research among human resource professionals in Thailand, this article develops a practitioner-oriented approach to responsible AI adoption. The study identifies perceived ethical governance as the largest positive predictor of adoption intention within its tested model, while also documenting resource constraints and capability gaps. These findings are interpreted alongside research on technology acceptance, algorithmic hiring, organizational control, and human–AI collaboration. The article proposes three complementary organizational priorities: establish accountable decision-making, develop the capability to question AI, and require evidence before expanding deployment. Organizational practices from technology, banking, and healthcare illustrate how these priorities can be operationalized. The central argument is that governance should enable justified adoption—not merely greater adoption—while protecting employees, candidates, and the organization from avoidable harm.