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◆ Knowledge and Process Management2026-05-04· Knowledge management

Revolutionizing <scp>AI</scp> ‐Driven <scp>HR</scp> Transformation: A Study on Enhancing Workforce Efficiency Through the Technology Task Fit Framework

Manali Chowdhury, Soumya Mukherjee, Mrinal Kanti Das, Udit Chawla

原始摘要(英文原文)· Original abstract
ABSTRACT Artificial intelligence (AI) is increasingly embedded in human resource management (HRM), yet evidence remains limited on how its value is realized across interconnected HR processes. This study examines whether AI adoption is associated with perceived effectiveness across major HR domains in Indian IT and IT‐enabled service firms and whether AI‐Empowered Decision‐Making helps explain this relationship. Guided by Technology‐Task Fit (TTF) as an organizing lens, the study adopts a cross‐sectional quantitative design based on survey data from 287 respondents and uses structural equation modeling to test the proposed relationships. The findings show that AI adoption is positively associated with all examined HR process outcomes, although the strength of these relationships varies across domains. AI‐Empowered Decision‐Making also shows a significant mediating effect in the relationship between AI adoption and Efficient HR Practices. The study contributes to research on AI‐enabled HRM by showing that the value of AI is not explained by adoption alone, but by how AI‐supported insights are translated into managerial action across HR processes. These findings support a more process‐oriented understanding of AI in HRM and highlight the importance of decision routines in realizing process‐level value.
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Revolutionizing <scp>AI</scp> ‐Driven <scp>HR</scp> Transformation: A Study on Enhancing Workforce Efficiency Through the Technology Task Fit Framework — 科研速览 Science Skim