Imagining AI at work: the impact of polarized imaginaries on AI use in human resources management

Purpose The purpose of this study is to investigate how polarized imaginaries about the future of artificial intelligence (AI) for work impact AI practices in Human Resources Management (HRM). In doing so, this study provides insights into the influence replacement narratives have on AI use, showing that AI imaginaries can be understood as social practice imaginaries emerging from the present. Design/methodology/approach The study is based on 20 interviews with HRM practitioners in Italy and two organizational observations with companies using AI in the recruitment process. The use of interviews and observations together has allowed to gather information about both HR practitioners’ expectations and emerging practices. Findings The results show that HR practitioners negotiate replacement narratives against the backdrop of their own experience in using AI. Learning is adopted as a strategy to protect themselves from replacement, while popular fears and hopes are delayed as the current AI capabilities do not fulfill their promises. AI becomes a useful tool allowing them to dedicate themselves to meaningful tasks contributing to their self-actualization. From these emerging practices stems an alternative imaginary of AI, positioning workers’ wellbeing at the center of automation. Originality/value This study challenges narratives on the future of AI for work by providing empirical evidence of their negotiation by workers and intersecting them with research on social practices. By doing so, it proposes an alternative imaginary of the future of AI in the workplace that moves away from traditional expectations about replacement and invites reflection on workers’ needs.

Authors

Institutions

Publication Details

Journal
Journal of Workplace Learning
Published
2026-01-08
DOI
https://doi.org/10.1108/jwl-06-2025-0162
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Imagining AI at work: the impact of polarized imaginaries on AI use in human resources management

Silvia Ecclesia
Journal of Workplace Learning
Ethics and Social Impacts of AI
article

Imagining AI at work: the impact of polarized imaginaries on AI use in human resources management

Silvia Ecclesia
article en

Abstract

Purpose The purpose of this study is to investigate how polarized imaginaries about the future of artificial intelligence (AI) for work impact AI practices in Human Resources Management (HRM). In doing so, this study provides insights into the influence replacement narratives have on AI use, showing that AI imaginaries can be understood as social practice imaginaries emerging from the present. Design/methodology/approach The study is based on 20 interviews with HRM practitioners in Italy and two organizational observations with companies using AI in the recruitment process. The use of interviews and observations together has allowed to gather information about both HR practitioners’ expectations and emerging practices. Findings The results show that HR practitioners negotiate replacement narratives against the backdrop of their own experience in using AI. Learning is adopted as a strategy to protect themselves from replacement, while popular fears and hopes are delayed as the current AI capabilities do not fulfill their promises. AI becomes a useful tool allowing them to dedicate themselves to meaningful tasks contributing to their self-actualization. From these emerging practices stems an alternative imaginary of AI, positioning workers’ wellbeing at the center of automation. Originality/value This study challenges narratives on the future of AI for work by providing empirical evidence of their negotiation by workers and intersecting them with research on social practices. By doing so, it proposes an alternative imaginary of the future of AI in the workplace that moves away from traditional expectations about replacement and invites reflection on workers’ needs.

Journal of Workplace Learning
Norwegian University of Science and Technology (NO)
Openalex Percentile: Top 94%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.