Aggrandizing the human resource development with underpinning artificial intelligence. Issue 5 (4th July 2022)
- Record Type:
- Journal Article
- Title:
- Aggrandizing the human resource development with underpinning artificial intelligence. Issue 5 (4th July 2022)
- Main Title:
- Aggrandizing the human resource development with underpinning artificial intelligence
- Authors:
- Lilly, A.
Rajkumar, R.
Amudha, R. - Abstract:
- Abstract: In the present time, humans could sense the presence of Artificial Intelligence in all facets of their lives. We no longer need to wonder whether AI is revolutionizing the modern workplace. The hearsay question is whether AI will replace human workers hoists far and wide. If truth be told, the genuine examination must be made on how AI can be availed to foster, not supersede, the human workforce, is conducive to make employees work zippier, more dexterously, and efficaciously. In this context, Human Resource Development is essential for bridging the differences. Given that HRD emphasizes human factors, it is not surprising why it is creating curiosity about how Artificial Intelligence based Human Resource Development works. By leveraging Machine Learning and Artificial Intelligence (AI), organizations can modernize operations, foster talent management and scale down Employee turnover. As a Human Resource Development approach, this paper examines the theoretical background with regard to AI and analyses the window of opportunity that AI opens for us.
- Is Part Of:
- Journal of statistics & management systems. Volume 25:Issue 5(2022)
- Journal:
- Journal of statistics & management systems
- Issue:
- Volume 25:Issue 5(2022)
- Issue Display:
- Volume 25, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 25
- Issue:
- 5
- Issue Sort Value:
- 2022-0025-0005-0000
- Page Start:
- 1083
- Page End:
- 1094
- Publication Date:
- 2022-07-04
- Subjects:
- 91C05 and 62P25
Artificial intelligence -- Machine learning -- Human resource development -- Talent management -- Employee turnover
Statistics -- Periodicals
Mathematical models -- Periodicals
Mathematical models
Statistics
Periodicals
519.5 - Journal URLs:
- http://www.tandfonline.com/loi/tsms20 ↗
- DOI:
- 10.1080/09720510.2022.2040859 ↗
- Languages:
- English
- ISSNs:
- 0972-0510
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23905.xml