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Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes
In recent years artificial intelligence (AI) has been seen as a technology with tremendous potential for enabling companies to gain an operational and competitive advantage. However, despite the use of AI, businesses continue to face challenges and are unable to immediately realize performance gains...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9018249/ https://www.ncbi.nlm.nih.gov/pubmed/35464171 http://dx.doi.org/10.1007/s10796-022-10251-y |
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author | Papagiannidis, Emmanouil Enholm, Ida Merete Dremel, Chirstian Mikalef, Patrick Krogstie, John |
author_facet | Papagiannidis, Emmanouil Enholm, Ida Merete Dremel, Chirstian Mikalef, Patrick Krogstie, John |
author_sort | Papagiannidis, Emmanouil |
collection | PubMed |
description | In recent years artificial intelligence (AI) has been seen as a technology with tremendous potential for enabling companies to gain an operational and competitive advantage. However, despite the use of AI, businesses continue to face challenges and are unable to immediately realize performance gains. Furthermore, firms need to introduce robust AI systems and mitigate AI risks, which emphasizes the importance of creating suitable AI governance practices. This study, explores how AI governance is applied to promote the development of robust AI applications that do not introduce negative effects, based on a comparative case analysis of three firms in the energy sector. The study illustrates which practices are placed to produce knowledge that assists with decision making while at the same time overcoming barriers with recommended actions leading to desired outcomes. The study contributes by exploring the main dimensions relevant to AI’s governance in organizations and by uncovering the practices that underpin them. |
format | Online Article Text |
id | pubmed-9018249 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-90182492022-04-20 Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes Papagiannidis, Emmanouil Enholm, Ida Merete Dremel, Chirstian Mikalef, Patrick Krogstie, John Inf Syst Front Article In recent years artificial intelligence (AI) has been seen as a technology with tremendous potential for enabling companies to gain an operational and competitive advantage. However, despite the use of AI, businesses continue to face challenges and are unable to immediately realize performance gains. Furthermore, firms need to introduce robust AI systems and mitigate AI risks, which emphasizes the importance of creating suitable AI governance practices. This study, explores how AI governance is applied to promote the development of robust AI applications that do not introduce negative effects, based on a comparative case analysis of three firms in the energy sector. The study illustrates which practices are placed to produce knowledge that assists with decision making while at the same time overcoming barriers with recommended actions leading to desired outcomes. The study contributes by exploring the main dimensions relevant to AI’s governance in organizations and by uncovering the practices that underpin them. Springer US 2022-04-20 2023 /pmc/articles/PMC9018249/ /pubmed/35464171 http://dx.doi.org/10.1007/s10796-022-10251-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Papagiannidis, Emmanouil Enholm, Ida Merete Dremel, Chirstian Mikalef, Patrick Krogstie, John Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title | Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title_full | Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title_fullStr | Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title_full_unstemmed | Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title_short | Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes |
title_sort | toward ai governance: identifying best practices and potential barriers and outcomes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9018249/ https://www.ncbi.nlm.nih.gov/pubmed/35464171 http://dx.doi.org/10.1007/s10796-022-10251-y |
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