Impacts of artificial intelligence on an HR generalist role

Lamper Ágnes (2026) Impacts of artificial intelligence on an HR generalist role. Prosperitas, early access online. pp. 1-15. ISSN 2786-4359 (Online)

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Abstract

This study explores how artificial intelligence (AI) impacts competencies in the HR generalist role. It addresses a critical gap in understanding the evolving nature of HR work in AI‐integrated environments. Adopting a qualitative design, 11 semi‐structured interviews analyzed with GIOIA methodology revealed how AI influences HR competencies through emergent concepts and themes. AI automates routine tasks and enhances strategic HR functions through analytics and decision support. It introduces new technical and ethical skills, yet human-centric competencies like empathy and negotiation remain essential to HR’s relational core. The study’s reliance on a small, purposively selected sample and its qualitative design limit the generalizability of findings across all organizational contexts, industries, and geographic regions. Implications. The results advocate for clear AI governance frameworks, ethical guidelines, and the cultivation of internal AI champions. They underscore the urgency of targeted reskilling programs that balance technological fluency with strategic and interpersonal capabilities, ensuring the human essence of HR endures amid accelerating automation. This research contributes a novel five-dimension conceptual framework that captures AI’s multifaceted impact on HR generalist competencies, advancing the discourse on hybrid HR professionalism that integrates emotional intelligence, strategic acumen, and technological fluency

Tudományterület / tudományág

társadalomtudományok > gazdálkodás- és szervezéstudományok

Intézmény

Budapesti Gazdasági Egyetem

Mű típusa:	Cikk
Szerző publikációban használt neve:	Publikációban használt név ORCID MTMT szerző azonosító Lamper Ágnes https://orcid.org/0009-0004-9169-0074
Kulcsszavak:	HR competencies, artificial intelligence, HR generalists, strategic HR, organizational change
Felhasználó:	Kinga Eszenyi-Bakos
A mű MTMT azonosítója:	36853239
DOI azonosító:	https://doi.org/10.31570/prosp_2026_173
Rekord készítés dátuma:	2025. Szep. 17. 08:16
Utolsó módosítás:	2026. Jan. 08. 13:26
URI:	https://publikaciotar.uni-bge.hu/id/eprint/2558

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