Alebri, Ahmed Mohamed (2022) The Impact of artificial intelligence on the employee engagement: a study of oil and gas originations of UAE. Doctoral thesis, University of Wales Trinity Saint David.
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Final Dissertation Ahmed ALEbri 14 November 2022.pdf - Accepted Version Restricted to Repository staff only Available under License CC-BY-NC-ND Creative Commons Attribution Non-commercial No Derivatives. Download (3MB) | Request a copy |
Abstract
The study aims to uncover how employees feel about the increasing focus of government for Artificial Intelligence in their country and what impact this will have on future careers. The literature shows there's a need for further research into understanding workers' plans or inability being facilitated by organizations/states if they're at risk due robotic technology that uses AI based primarily off data analysis, which could lead them with no jobs available. Artificial intelligence is quickly becoming one of the most prominent trends in today's workplace. While this technology has many benefits, it also poses some risks for employees who may not be able to find employment ten years from now if their jobs fall victim to robotic automation or machines that can replace human workers with minimal effort on behalf. This study aims at uncovering what people think about AI-based robotic technologies which could spell danger downgrading certain jobs and how they plan themselves accordingly given current circumstances. The findings of this study show that many employees are considering learning new skills and enhancing their performance at work. In addition, they plan on attending more training programs in order to keep up with the AI-related changes happening around them while also saving themselves from possible unemployment after its implementation into society as well. The proportion however is not very high but there's always hope for those who want it. Keywords: Artificial Intelligence, human employees, employee engagement, future employability, Abu Dhabi, United Arab Emirates
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Politics, News, Television, UAE |
| Subjects: | D History General and Old World > DS Asia H Social Sciences > HD Industries. Land use. Labor |
| Divisions: | Theses and Dissertations > Doctoral Theses |
| Depositing User: | Ahmed Alebri |
| Date Deposited: | 05 Jan 2023 10:04 |
| Last Modified: | 05 Jan 2023 10:07 |
| URI: | https://repository.uwtsd.ac.uk/id/eprint/2205 |
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