The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes
This thesis examines the importance of artificial intelligence (AI) in reducing negative human intervention in recruitment and selection processes. The study uses a sequential approach to analyse the impact of ICT, AI, and recruitment and selection components on recruitment and selection processes....
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2024
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| Online Access: | https://bspace.buid.ac.ae/handle/1234/3215 |
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| _version_ | 1862980615367819264 |
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| author | KHAWAN, SALIM SAEED THANI JUMA |
| author_facet | KHAWAN, SALIM SAEED THANI JUMA |
| author_role | author |
| dc.contributor.none.fl_str_mv | Dr Abdelmounaim Lahrech |
| dc.creator.none.fl_str_mv | KHAWAN, SALIM SAEED THANI JUMA |
| dc.date.none.fl_str_mv | 2024-11 2025-06-26T05:01:23Z 2025-06-26T05:01:23Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 20181337 https://bspace.buid.ac.ae/handle/1234/3215 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| dc.title.none.fl_str_mv | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| dc.type.none.fl_str_mv | Thesis |
| description | This thesis examines the importance of artificial intelligence (AI) in reducing negative human intervention in recruitment and selection processes. The study uses a sequential approach to analyse the impact of ICT, AI, and recruitment and selection components on recruitment and selection processes. Data were collected through questionnaires distributed to employees of specific categories in Sharjah Government institutions in the UAE, with 251 participants agreeing to answer. The aim of the study is to respond to the research questions and hypotheses, engage in discussions, make practical contributions, and formulate recommendations. The literature review highlights the practical value of AI in selecting competent candidates for job vacancies in institutions. The research sheds light on the significance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study uses various statistical techniques such as structural equation modelling (SEM) analysis, multiple linear regression (MLR), descriptive and inferential statistics, and confirmatory factor analysis to identify the impact of AI on recruitment and selection processes. The results indicate that the use of AI to filter the CVs of job seekers and select qualified candidates for vacancies was perceived positively at a high level of significance (p ≤ 0.05), leading to reduced human errors in the process. The participants believed that most HR operations management in the future could depend on AI without human intervention. The research participants’ responses to using technology to enhance recruitment and selection processes were at a high level of significance (p ≤ 0.05). The participants also perceived the negative impact of key members on recruitment and selection processes at a high level of significance (p ≤ 0.05). The research proposes a framework for AI-assisted recruitment and selection processes, aiming to reduce errors and improve the selection of qualified candidates. It emphasises the need for institutions to establish new employment standards based on the use of AI technology and outlines key elements required for successful implementation, including infrastructure, specialised partnerships, employment platforms, and policy and regulation amendments. Overall, this study highlights the increasing significance of AI in enterprise operations and the need for researchers and specialists to consider AI as a key element for supporting production and services. The research sheds light on the importance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study was conducted with 251 participants from Sharjah Government institutions in the UAE, and the data were analysed using Statistical Package for Social Sciences (SPSS) software version 23 and STATA/MP software version 13.0. |
| id | budr_b239d97a0f6d7fa0865a0be9e4e2260d |
| identifier_str_mv | 20181337 |
| language_invalid_str_mv | en |
| network_acronym_str | budr |
| network_name_str | The British University in Dubai repository |
| oai_identifier_str | oai:bspace.buid.ac.ae:1234/3215 |
| publishDate | 2024 |
| publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | The Impact of Artificial Intelligence on Institutional Recruitment and Selection ProcessesKHAWAN, SALIM SAEED THANI JUMAThis thesis examines the importance of artificial intelligence (AI) in reducing negative human intervention in recruitment and selection processes. The study uses a sequential approach to analyse the impact of ICT, AI, and recruitment and selection components on recruitment and selection processes. Data were collected through questionnaires distributed to employees of specific categories in Sharjah Government institutions in the UAE, with 251 participants agreeing to answer. The aim of the study is to respond to the research questions and hypotheses, engage in discussions, make practical contributions, and formulate recommendations. The literature review highlights the practical value of AI in selecting competent candidates for job vacancies in institutions. The research sheds light on the significance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study uses various statistical techniques such as structural equation modelling (SEM) analysis, multiple linear regression (MLR), descriptive and inferential statistics, and confirmatory factor analysis to identify the impact of AI on recruitment and selection processes. The results indicate that the use of AI to filter the CVs of job seekers and select qualified candidates for vacancies was perceived positively at a high level of significance (p ≤ 0.05), leading to reduced human errors in the process. The participants believed that most HR operations management in the future could depend on AI without human intervention. The research participants’ responses to using technology to enhance recruitment and selection processes were at a high level of significance (p ≤ 0.05). The participants also perceived the negative impact of key members on recruitment and selection processes at a high level of significance (p ≤ 0.05). The research proposes a framework for AI-assisted recruitment and selection processes, aiming to reduce errors and improve the selection of qualified candidates. It emphasises the need for institutions to establish new employment standards based on the use of AI technology and outlines key elements required for successful implementation, including infrastructure, specialised partnerships, employment platforms, and policy and regulation amendments. Overall, this study highlights the increasing significance of AI in enterprise operations and the need for researchers and specialists to consider AI as a key element for supporting production and services. The research sheds light on the importance of AI in recruitment and selection processes, providing insights into how it can improve the efficiency and accuracy of selection procedures while reducing human biases. The study was conducted with 251 participants from Sharjah Government institutions in the UAE, and the data were analysed using Statistical Package for Social Sciences (SPSS) software version 23 and STATA/MP software version 13.0.The British University in Dubai (BUiD)Dr Abdelmounaim Lahrech2025-06-26T05:01:23Z2025-06-26T05:01:23Z2024-11Thesisapplication/pdf20181337https://bspace.buid.ac.ae/handle/1234/3215enoai:bspace.buid.ac.ae:1234/32152025-07-23T08:27:49Z |
| spellingShingle | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes KHAWAN, SALIM SAEED THANI JUMA |
| title | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| title_full | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| title_fullStr | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| title_full_unstemmed | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| title_short | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| title_sort | The Impact of Artificial Intelligence on Institutional Recruitment and Selection Processes |
| url | https://bspace.buid.ac.ae/handle/1234/3215 |