The accelerated adoption of Artificial Intelligence (AI) in recruitment has outpaced ethical governance with persistent gaps in oversight and explainability. This qualitative descriptive case study examined the influence of AI on recruitment processes, focusing on how organizational actors implement, govern, and experience AI in hiring. Data comprised semi-structured, web-based interviews with 10 participants, including HR leaders, diversity practitioners, and AI developers from the Southern United States, as well as document analysis. The document corpus, including 13 company policies, 7 governmental/regulatory sources, and 5 quasi-governmental sources, was used for context and triangulation. Analysis followed Braun and Clarke’s reflexive thematic analysis in NVivo and was interpreted through Socio-Technical Systems (STs) and the Ethics of Care (EoC) theories to prioritize human judgment and candidate dignity. Findings identified eight cross-cutting themes, including candidate experience and personalization, efficiency and innovation, human oversight and safeguards, fairness and inclusion, ethics and accountability, risks of misuse and bias, transparency and trust, and escalation protocols. Participants perceived the value of AI as inseparable from disciplined human stewardship, formalized governance routines, and auditable accountability mechanisms aimed to preserve candidate dignity. The study offers practice-ready recommendations for leaders and practitioners, including plain-language transparency standards, documented human review at AI-affected decision points, and accessible redress pathways to support responsible and equitable adoption. Transferability is bounded by the single-case design and context, indicating the need for multi-site and longitudinal inquiry to extend these insights.