Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector
This research examines factors influencing AI implementation effectiveness in the public sector. Governments globally compete to advance public sector services and transform public services to digital to fulfil continuous citizens and business demands to reach the expectation of state-of-the-art ser...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://bspace.buid.ac.ae/handle/1234/2533 |
| الوسوم: |
إضافة وسم
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| _version_ | 1862980610208825344 |
|---|---|
| author | ALAWADHI, JASSIM |
| author_facet | ALAWADHI, JASSIM |
| author_role | author |
| dc.contributor.none.fl_str_mv | Professor Stephen Wilkins |
| dc.creator.none.fl_str_mv | ALAWADHI, JASSIM |
| dc.date.none.fl_str_mv | 2023-10 2024-03-18T06:41:28Z 2024-03-18T06:41:28Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 20000668 https://bspace.buid.ac.ae/handle/1234/2533 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | The British University in Dubai (BUiD) |
| dc.subject.none.fl_str_mv | artificial intelligence, public sector, adoption, implementation |
| dc.title.none.fl_str_mv | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| dc.type.none.fl_str_mv | Thesis |
| description | This research examines factors influencing AI implementation effectiveness in the public sector. Governments globally compete to advance public sector services and transform public services to digital to fulfil continuous citizens and business demands to reach the expectation of state-of-the-art services. Thus, governments worldwide are racing to utilise advanced Information and Communication Technologies (ICT). Hence, governments implement Artificial Intelligence systems to develop cutting-edge platforms, serving as a base for the government's journey to AI-based government transformation. Existing literature reveals that organisations' cognitive technology projects fail to meet their successful implementation. Therefore, the AI-deployed system fails to deliver the expected performance and objective outcome. Further, scholars discuss gaps in AI field literature and reveal the absence of public sector articles since most AI articles are technical. Also, there is a literature gap in empirical quantitative theory-based research and research measuring the effectiveness of AI system implementation. Moreover, scholars reveal that nations' AI strategies are inspirational and lack implementation guidance. Consequently, this research aims to fill the gap in the literature by creating a theory-based, quantitative study to examine factors that influence the implementation effectiveness of Artificial Intelligence in the public sector at the organisational level from a technology, organisation, and environment perspective. Based on the extensive literature review, the thesis formulates a theoretical framework that combines the Diffusion of Innovation Theory (DOI), the Institutional Theory (INT), and the Technology – Organisation – Environment Framework (T.O.E) to act as the researcher's lens to view the study world. This study tested hypotheses based on literature and existing theories. Hence, the researcher adopted objectivist worldwide ontology, positivist epistemology, explanatory deductive reasoning, and a quantitative method as study philosophy to examine the relationship between the study factors. The research findings indicate a significant relationship between study factors. However, the results show a lack of significance between technology compatibility, usability, and effectiveness of AI implementation. Further, the study results reveal an insignificant relationship between culture impact and AI implementation effectiveness in the UAE public sector. The research implies that public sector top management is critical to AI system implementation; therefore, public sector top management must have cognitive technology knowledge and understand the Technology – organisation – Environment aspects for implementing AI systems. To effectively implement AI systems, top management should plan strategically to retain organisation data with quality, create a collaborative culture, strategically demonstrate the organisation's competitive advantage, cooperate with human resources to hire AI expertise to lead AI-based projects and adopt an implementation framework. |
| id | budr_b1312da7545c3d58ff3ecc407af64ab2 |
| identifier_str_mv | 20000668 |
| 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:1234/2533 |
| publishDate | 2023 |
| 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 | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public SectorALAWADHI, JASSIMartificial intelligence, public sector, adoption, implementationThis research examines factors influencing AI implementation effectiveness in the public sector. Governments globally compete to advance public sector services and transform public services to digital to fulfil continuous citizens and business demands to reach the expectation of state-of-the-art services. Thus, governments worldwide are racing to utilise advanced Information and Communication Technologies (ICT). Hence, governments implement Artificial Intelligence systems to develop cutting-edge platforms, serving as a base for the government's journey to AI-based government transformation. Existing literature reveals that organisations' cognitive technology projects fail to meet their successful implementation. Therefore, the AI-deployed system fails to deliver the expected performance and objective outcome. Further, scholars discuss gaps in AI field literature and reveal the absence of public sector articles since most AI articles are technical. Also, there is a literature gap in empirical quantitative theory-based research and research measuring the effectiveness of AI system implementation. Moreover, scholars reveal that nations' AI strategies are inspirational and lack implementation guidance. Consequently, this research aims to fill the gap in the literature by creating a theory-based, quantitative study to examine factors that influence the implementation effectiveness of Artificial Intelligence in the public sector at the organisational level from a technology, organisation, and environment perspective. Based on the extensive literature review, the thesis formulates a theoretical framework that combines the Diffusion of Innovation Theory (DOI), the Institutional Theory (INT), and the Technology – Organisation – Environment Framework (T.O.E) to act as the researcher's lens to view the study world. This study tested hypotheses based on literature and existing theories. Hence, the researcher adopted objectivist worldwide ontology, positivist epistemology, explanatory deductive reasoning, and a quantitative method as study philosophy to examine the relationship between the study factors. The research findings indicate a significant relationship between study factors. However, the results show a lack of significance between technology compatibility, usability, and effectiveness of AI implementation. Further, the study results reveal an insignificant relationship between culture impact and AI implementation effectiveness in the UAE public sector. The research implies that public sector top management is critical to AI system implementation; therefore, public sector top management must have cognitive technology knowledge and understand the Technology – organisation – Environment aspects for implementing AI systems. To effectively implement AI systems, top management should plan strategically to retain organisation data with quality, create a collaborative culture, strategically demonstrate the organisation's competitive advantage, cooperate with human resources to hire AI expertise to lead AI-based projects and adopt an implementation framework.The British University in Dubai (BUiD)Professor Stephen Wilkins2024-03-18T06:41:28Z2024-03-18T06:41:28Z2023-10Thesisapplication/pdf20000668https://bspace.buid.ac.ae/handle/1234/2533enoai:bspace.buid.ac.ae:1234/25332024-03-18T23:00:17Z |
| spellingShingle | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector ALAWADHI, JASSIM artificial intelligence, public sector, adoption, implementation |
| title | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| title_full | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| title_fullStr | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| title_full_unstemmed | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| title_short | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| title_sort | Analysing Factors Influencing AI Implementation Effectiveness in the UAE Public Sector |
| topic | artificial intelligence, public sector, adoption, implementation |
| url | https://bspace.buid.ac.ae/handle/1234/2533 |