Transforming Key Industries in Rivers State: The Impact of Automation and Artificial Intelligence on the Future of Work

Onyekwere, Lawretta Adaobi (2024) Transforming Key Industries in Rivers State: The Impact of Automation and Artificial Intelligence on the Future of Work. Journal of Basic and Applied Research International, 30 (3). pp. 35-57. ISSN 2395-3446

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The study investigated automation, artificial intelligence and the future of work in key industries in Rivers State. Four research questions and four corresponding hypotheses were formulated to understand how AI automation relationship s job security, skill requirements, workforce adaptation, employee well-being, and work-life balance in these industries. The research uses a correlational research design and the target population comprises employees from key industries in Rivers State, including manufacturing, agriculture, healthcare, and technology sectors. A stratified random sampling technique was employed to draw a sample size of 54 employees across these industries. The self-structured questionnaire titled “Automation and Artificial Intelligence Integration in Industries Questionnaire (AAIIIQ)” and “Future of Work Questionnaire (FWQ)” using a 4-point Likert scale ranging from Very Low Extent (1) to Very High Extent (4). The questionnaire was distributed within the dry season of November 2023 to February 2024. During this period, 54 copies were distributed, but only 49 were returned. Of these, 2 were not correctly filled out, leaving the researcher with only 47 valid copies that were used for data analysis. To ensure content validity, the questionnaire was reviewed by experts in the field of Organizational Behaviour and Information and Communication Technology (ICT). The reliability of the instrument was assessed using the test-retest method with a sample of 10 participants which were not part of the main sample size, but within the study’s population. The questionnaire was distributed twice at a two-week interval, and the responses were analyzed using the Pearson Product-Moment Correlation (PPMC). A reliability index of .87 was calculated based on the outcomes of this analysis. Mean and standard deviation, was used to answer the research questions, Pearson’s Product-Moment Correlation (PPMC), was utilized to test hypotheses at a significance level of 0.05. The findings underscore the critical importance of considering the effects of AI automation on job security, workforce adaptation, employee well-being, and organizational strategies. Conclusion, the study’s findings underscore the transformative nature of AI automation on the future of work in key industries in Rivers State. By recognizing and responding to these changes, organizations can harness the full potential of AI automation while mitigating its potential negative impacts. The study recommended that organizations should prioritize employee training and development, offering opportunities for upskilling and reskilling to ensure their workforce remains competitive and adaptable to technological advancements.

Item Type: Article
Subjects: STM Repository > Multidisciplinary
Depositing User: Managing Editor
Date Deposited: 08 Jul 2024 07:44
Last Modified: 08 Jul 2024 07:44

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