<![CDATA[The rapid digitalization of administrative services in higher education has accelerated the adoption of artificial intelligence (AI), fundamentally reshaping the competencies required of administrative staff. While previous research has largely focused on AI’s implications for teaching and learning, relatively little is known about how non-academic administrative personnel adapt to AI-enabled environments. This qualitative study explores the competencies needed by administrative staff to sustain accuracy, responsiveness, and accountability in an increasingly automated institutional landscape. Guided by Creswell’s qualitative research design, data were collected through semi-structured interviews with administrative staff across multiple units in a higher education institution. Thematic analysis following Braun and Clarke’s reflexive approach generated four interrelated themes. Findings show that administrative roles have expanded beyond procedural tasks toward interpretive, supervisory, and evaluative functions, requiring staff to understand how AI systems operate, validate AI outputs, and intervene in cases requiring contextual judgment. Data literacy emerged as critical for ensuring the accuracy and integrity of institutional reporting, while human oversight was essential for maintaining ethical and contextually appropriate decision-making. Continuous learning—supported by structured training and organizational mechanisms—proved indispensable for sustaining these competencies. The study contributes to current debates on AI in higher education by highlighting the multidimensional and socio-technical nature of administrative competency in the AI era and offers practical recommendations for workforce development and institutional policy.]]>
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