How organizations’ technological orientation shapes job seekers’ responses toward AI

Scholars and practitioners are increasingly interested in the organizational costs and benefits of incorporating artificial intelligence (AI) into hiring practices. Job seekers, meanwhile, have shown ambivalence toward companies’ use of this new technology, but is this true for all types of organizations? Drawing on the Computers Are Social Actors (CASA) framework and cognitive dissonance theory, we investigate how an organization’s technological orientation shapes job seekers’ perceptions of, and intentions toward, the use of AI in hiring. Across four controlled experiments, we find that job seekers are less willing to apply to low-tech (vs. high-tech) organizations that use AI-based (vs. human-based) selection processes (Study 1). This effect arises from job seekers’ lower perceived fluency between the organization’s technological orientation and the selection process (Study 2), which in turn induces cognitive dissonance and decreases their willingness to apply (Study 3a). Finally, the results indicate that these effects generalize across different organizational contexts (Study 3b). Our research contributes to the literature on AI acceptance in recruitment by integrating organizational-level and psychological explanations of job seekers’ responses to AI, offering practical insights for human resources (HR) professionals seeking to effectively implement AI in hiring.

Authors

Institutions

Publication Details

Journal
The International Journal of Human Resource Management
Published
2025-11-13
DOI
https://doi.org/10.1080/09585192.2026.2620717
Primary Topic
Employer Branding and e-HRM
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How organizations’ technological orientation shapes job seekers’ responses toward AI

Rumen Pozharliev, Roberto Urbani, Matteo De Angelis, Valerio Deriu
The International Journal of Human Resource Management
Employer Branding and e-HRM
article

How organizations’ technological orientation shapes job seekers’ responses toward AI

Rumen Pozharliev, Roberto Urbani, Matteo De Angelis, Valerio Deriu
article en

Abstract

Scholars and practitioners are increasingly interested in the organizational costs and benefits of incorporating artificial intelligence (AI) into hiring practices. Job seekers, meanwhile, have shown ambivalence toward companies’ use of this new technology, but is this true for all types of organizations? Drawing on the Computers Are Social Actors (CASA) framework and cognitive dissonance theory, we investigate how an organization’s technological orientation shapes job seekers’ perceptions of, and intentions toward, the use of AI in hiring. Across four controlled experiments, we find that job seekers are less willing to apply to low-tech (vs. high-tech) organizations that use AI-based (vs. human-based) selection processes (Study 1). This effect arises from job seekers’ lower perceived fluency between the organization’s technological orientation and the selection process (Study 2), which in turn induces cognitive dissonance and decreases their willingness to apply (Study 3a). Finally, the results indicate that these effects generalize across different organizational contexts (Study 3b). Our research contributes to the literature on AI acceptance in recruitment by integrating organizational-level and psychological explanations of job seekers’ responses to AI, offering practical insights for human resources (HR) professionals seeking to effectively implement AI in hiring.

The International Journal of Human Resource ManagementVol. 36(20)
Campus Bio Medico University Hospital (IT), Libera Università Internazionale degli Studi Sociali Guido Carli (IT)
Openalex Percentile: Top 19%
Employer Branding and e-HRM
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.