Conference paper 2024

Evaluating the Influence of Artificial Intelligence on Workforce Productivity at Small and Medium-Sized Enterprises

2024 International Conference on Decision Aid Sciences and Applications, DASA 2024
Conference
Abstract

The research being conducted aims to examine the impact of artificial intelligence (AI) on labour productivity inside small and medium-sized enterprises (SMEs) situated in Bahrain. Utilising a carefully constructed questionnaire with a solid reliability value (Cronbach's Alpha = 0.974), data was collected from the staff of this sector. The findings of our study indicate that the integration of artificial intelligence (AI) significantly enhances productivity, as it amplifies the benefits of training. Corroborating previous studies, the results indicate that targeted training improves performance and that artificial intelligence has the potential to automate tasks and provide personalized learning experiences. The present study addresses the existing research deficiencies in the domain of small and medium-sized companies (SMEs) and the synergistic effects of artificial intelligence (AI). The pragmatic implications suggest that small and medium-sized firms (SMEs) could make use of artificial intelligence (AI) to augment training programmes and boost productivity. © 2024 IEEE.

Keywords

Author Keywords

Training Artificial intelligence data analysis SMEs Bahrain Employee Productivity

Index Keywords

Personnel training Labour productivities Personalized learning Learning experiences small and medium-sized enterprise Bahrain Cronbach's alphas Employee productivity Improve performance Reliability values Small and medium-sized companies
Author Affiliations
Department of Business Administration, Applied Science University, Al Eker, Bahrain
College of Administrative and Financial Science, Gulf University, Sanad, Bahrain
College of Information Technology, University of Bahrain, Zallaq, Bahrain
University of Dubai, Dubai, United Arab Emirates
Funding & Acknowledgements
No funding information
References 10 References
1 Almohammadi, Khalid, A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms, Journal of Artificial Intelligence and Soft Computing Research, 7, 1, pp. 47-64, (2017)
2 Gligorea, Ilie, Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review, Education Sciences, 13, 12, (2023)
3 Ibrahim, Ishaq, How Does Chat GPT Influence Human Capital Development Amongst Malaysian Undergraduate Students?, 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024, pp. 213-219, (2024)
4 Maity, Souvik, Identifying opportunities for artificial intelligence in the evolution of training and development practices, Journal of Management Development, 38, 8, pp. 651-663, (2019)
5 Jalal, Arif Hanafi Bin, Empowering Early Career Neurosurgeons in the Critical Appraisal of Artificial Intelligence and Machine Learning: The Design and Evaluation of a Pilot Course, World Neurosurgery, 190, pp. e537-e547, (2024)
6 Allam, Ahmed Hafez, Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study, European Radiology, 34, 7, pp. 1-14, (2024)
7 AI Society, (2024)
8 Artificial Intelligence in Modern Digital Marketing, (2024)
9 Chowdhury, Soumyadeb, Unlocking the value of artificial intelligence in human resource management through AI capability framework, Human Resource Management Review, 33, 1, (2023)
10 Journal of Service Research, (2024)
Quick Actions
Full Text via DOI
Citation Metrics
1
Times Cited (Scopus)

References 10
Document Identifiers