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Implementations of Artificial Intelligence in Various Domains of IT Governance: A Systematic Literature Review

Background: Artificial intelligence (AI) has become increasingly prevalent in various industries, including IT governance. By integrating AI into the governance environment, organizations can benefit from the consolidation of frameworks and best practices. However, the adoption of AI across differen...

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Bibliographic Details
Published in:Journal of information systems engineering and business intelligence 2023-11, Vol.9 (2), p.305-319
Main Authors: Hariyanti, Eva, Janeswari, Made Balin, Moningka, Malvin Mikhael, Aziz, Fikri Maulana, Putri, Annisa Rahma, Hapsari, Oxy Setyo, Sutha, Nyoman Agus Arya Dwija, Sinaga, Yohannes Alexander Agusti, Bendesa, Manik Prasanthi
Format: Article
Language:English
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Summary:Background: Artificial intelligence (AI) has become increasingly prevalent in various industries, including IT governance. By integrating AI into the governance environment, organizations can benefit from the consolidation of frameworks and best practices. However, the adoption of AI across different stages of the governance process is unevenly distributed. Objective: The primary objective of this study is to perform a systematic literature review on applying artificial intelligence (AI) in IT governance processes, explicitly focusing on the Deming cycle. This study overlooks the specific details of the AI methods used in the various stages of IT governance processes. Methods: The search approach acquires relevant papers from Elsevier, Emerald, Google Scholar, Springer, and IEEE Xplore. The obtained results were then filtered using predefined inclusion and exclusion criteria to ensure the selection of relevant studies. Results: The search yielded 359 papers. Following our inclusion and exclusion criteria, we pinpointed 42 primary studies that discuss how AI is implemented in every domain of IT Governance related to the Deming cycle. Conclusion: We found that AI implementation is more dominant in the plan, do, and check stages of the Deming cycle, with a particular emphasis on domains such as risk management, strategy alignment, and performance measurement since most AI applications are not able to perform well in different contexts as well as the other usage driven by its unique capabilities. Keywords: Artificial Intelligence, Deming cycle, Governance, IT Governance domain, Systematic literature review
ISSN:2598-6333
2443-2555
DOI:10.20473/jisebi.9.2.305-319