{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T15:55:59Z","timestamp":1775922959456,"version":"3.50.1"},"reference-count":85,"publisher":"Emerald","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,2]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>The study examines HRM professionals\u2019 evaluation of AI as technology for the three key HR processes: talent acquisition\/recruitment, training and development, performance evaluation and employee engagement. It also examines the key implementation learnings of HRM professionals. The motivation of our study is that despite being a game-changing technology with the potential to transform the HRM landscape substantially, AI\u2019s use is impeded by several persistent challenges that must be continuously examined and mitigated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>The study uses a qualitative research design to understand participants\u2019 narratives, perceptions and contextual meanings based on their lived experiences. We collected qualitative data through a two-wave study from 30 HRM professionals to operationalize this approach. These textual responses were analyzed using Gioia et\u00a0al.\u2019s (2013) approach to code their data structure comprising aggregate dimensions, second-order themes and first-order concepts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>Our findings broadly unpack into two parts: (1) HRM professionals\u2019 evaluation of AI as both an enabling and alienating technology, with different impacts across the three HRM processes and (2) HRM professionals\u2019 key implementation insights on internal contradictions and priorities, including AI-compatible HRM processes, human-in-the-loop approaches, organizational resistance and approaches to facilitate balanced integration of AI into HRM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>The study\u2019s novel contribution lies in (1) explicit mapping of the duality of AI-HRM to the three HRM processes, (2) formulation of a practice-oriented four-phase framework for AI integration in HRM and (3) proposal of \u201cStrategic Readiness\u201d as a theoretical construct for examining a firm\u2019s readiness to implement AI-HRM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1108\/jeim-03-2025-0139","type":"journal-article","created":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T15:36:35Z","timestamp":1751211395000},"page":"214-240","source":"Crossref","is-referenced-by-count":4,"title":["Managing human\u2013AI tensions in HRM: a learning approach to identify practical AI integration pathways"],"prefix":"10.1108","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2819-5685","authenticated-orcid":true,"given":"Shalini","family":"Talwar","sequence":"first","affiliation":[{"name":"Department of Finance and Accounting, S P Jain Institute of Management and Research (SPJIMR) , 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