The use of artificial intelligence (AI) in talent acquisition: The case of Greek luxury hotels

This study introduces a framework for the adoption of Artificial Intelligence (AI) driven technology to talent acquisition processes in luxury hotels. This qualitative study employed 23 semi-structured interviews to explore the perceptions of professionals on AI in luxury hotels in Greece. The findings highlight the benefits of AI-enabled technologies in talent acquisition, including speed, reliability and enhanced candidate communication, however, human interaction remains pivotal at critical stages. The model proposed includes six stages in the AI-Talent Acquisition process, serving as a practical guide for practitioners and researchers. This study contributes to the AI-HRM strategic change field by offering theoretical and practical insights. To the best of the authors' knowledge, it represents one of the initial empirical attempts to develop a comprehensive AI-Talent Acquisition framework, providing valuable implications for ongoing research and implementation in this domain.

Publication Details

Journal
Bournemouth University Research Online (Bournemouth University)
Published
2024-12-30
Primary Topic
Particle Detector Development and Performance
Type
article
Field-Weighted Citation Impact
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article

The use of artificial intelligence (AI) in talent acquisition: The case of Greek luxury hotels

Bournemouth University Research Online (Bournemouth University)
Particle Detector Development and Performance
article

The use of artificial intelligence (AI) in talent acquisition: The case of Greek luxury hotels

article en

Abstract

This study introduces a framework for the adoption of Artificial Intelligence (AI) driven technology to talent acquisition processes in luxury hotels. This qualitative study employed 23 semi-structured interviews to explore the perceptions of professionals on AI in luxury hotels in Greece. The findings highlight the benefits of AI-enabled technologies in talent acquisition, including speed, reliability and enhanced candidate communication, however, human interaction remains pivotal at critical stages. The model proposed includes six stages in the AI-Talent Acquisition process, serving as a practical guide for practitioners and researchers. This study contributes to the AI-HRM strategic change field by offering theoretical and practical insights. To the best of the authors' knowledge, it represents one of the initial empirical attempts to develop a comprehensive AI-Talent Acquisition framework, providing valuable implications for ongoing research and implementation in this domain.

Bournemouth University Research Online (Bournemouth University)
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Particle Detector Development and Performance
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