Assessing the Future of HRM: Exploring the Transformative Role of Artificial Intelligence in Realizing the UAE's Vision 2031 for AI-Driven Human Resources Practices

The current research was set to investigate the indirect impact of the adoption of AI in the UAE on AI-driven human resource management through the mediation of the Technology Acceptance Model. A total of 171 surveys were found to be valid and usable after being collected from human resource professionals working in both the Ministry of Energy and Infrastructure and the Ministry of Human Resources and Emiratization. We tested the hypotheses using SmartPLS4 software through partial least squares structural equation modeling (PLS-SEM). The research reported that AI adoption positively and significantly affects human resource management practices within the UAE. In addition, it had a great positive impact on the perceived usefulness and ease of use of AI in the UAE. Perceived ease of use, in turn, had a significant and positive impact on the attitude of users toward use and on perceived usefulness. Therefore, perceived usefulness had a substantial positive impact on attitudes and behavioral intentions of users in the use of AI technology. That is, user intentions significantly impacted the AI-driven HRM practices relating to the deployment of AI technology. So, the Technology Acceptance Model played a key role, leading to a notable indirect influence on AI-driven HRM practices in the UAE. Therefore, the integration of AI technology into human resources management has taken place.

Authors

Institutions

Publication Details

Journal
Qubahan Academic Journal
Published
2025-10-18
DOI
https://doi.org/10.48161/qaj.v5n4a1968
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the Future of HRM: Exploring the Transformative Role of Artificial Intelligence in Realizing the UAE's Vision 2031 for AI-Driven Human Resources Practices

Ahmed Attia, Abdelaziz El Fazziki, Ahmad Mousa, Ashraf Awad
Qubahan Academic Journal
Organizational and Employee Performance
article

Assessing the Future of HRM: Exploring the Transformative Role of Artificial Intelligence in Realizing the UAE's Vision 2031 for AI-Driven Human Resources Practices

Ahmed Attia, Abdelaziz El Fazziki, Ahmad Mousa, Ashraf Awad
article en

Abstract

The current research was set to investigate the indirect impact of the adoption of AI in the UAE on AI-driven human resource management through the mediation of the Technology Acceptance Model. A total of 171 surveys were found to be valid and usable after being collected from human resource professionals working in both the Ministry of Energy and Infrastructure and the Ministry of Human Resources and Emiratization. We tested the hypotheses using SmartPLS4 software through partial least squares structural equation modeling (PLS-SEM). The research reported that AI adoption positively and significantly affects human resource management practices within the UAE. In addition, it had a great positive impact on the perceived usefulness and ease of use of AI in the UAE. Perceived ease of use, in turn, had a significant and positive impact on the attitude of users toward use and on perceived usefulness. Therefore, perceived usefulness had a substantial positive impact on attitudes and behavioral intentions of users in the use of AI technology. That is, user intentions significantly impacted the AI-driven HRM practices relating to the deployment of AI technology. So, the Technology Acceptance Model played a key role, leading to a notable indirect influence on AI-driven HRM practices in the UAE. Therefore, the integration of AI technology into human resources management has taken place.

Qubahan Academic JournalVol. 5(4)
Abu Dhabi University (AE)
Openalex Percentile: Top 84%
Organizational and Employee Performance
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.