The future of sustainable human resource efficiency: A study on the impact of emerging digital tools

Authors

  • Dirar Abdelaziz Al-Maaitah Al Buraimi University College, Oman
  • Khaled Mohammad Alghraibeh Amman Arab University, Jordan
  • Mo'men Hani Mahmoud Middle East University, Jordan
  • Ahmad Rajaa Albatayneh Amman Arab University, Jordan

DOI:

https://doi.org/10.37868/hsd.v8i1.1629

Abstract

This article examines the impact of data analytics, artificial intelligence (AI) technology, and cloud computing on HR efficiency of Jordanian organizations, with emphasis on the moderating effects of information quality. A quantitative approach was utilized, and structured surveys were distributed to HR experts and HR managers who work in different industrial sectors in Jordan. Data from 415 valid respondents were statistically analyzed rigorously using the statistical software SPSS and AMOS, and were able to identify direct effects and moderation pathways. The study proves that operational efficiency in HR advances substantially by using data analytical systems with AI and cloud-based platforms. The quality of the data obtained acts as the fundamental element connecting organizational success. Organizations can fully benefit from digital transformation with proper data governance and consistent human resource data, but the absence or incorrect management blocks their advantages. Organizations should adopt digital technology as it depends on producing quality HR information to maximize HR efficiency. Jordanian businesses should invest in AI ethics, data governance, and cloud security measures to obtain the full advantages of digital transformation in HRM. The study presents applicable guidance for HR professionals, management executives, and governmental policymakers.

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Published

2026-01-15

How to Cite

[1]
D. A. Al-Maaitah, K. M. Alghraibeh, M. H. Mahmoud, and A. R. Albatayneh, “The future of sustainable human resource efficiency: A study on the impact of emerging digital tools”, Heritage and Sustainable Development, vol. 8, no. 1, pp. 1–16, Jan. 2026.

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Articles