Failure factors of AI projects: results from expert interviews
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://doi.org/10.12821/ijispm110302 |
Resumo: | In the last few years, business firms have substantially invested into the artificial intelligence (AI) technology. However, according to several studies, a significant percentage of AI projects fail or do not deliver business value. Due to the specific characteristics of AI projects, the existing body of knowledge about success and failure of information systems (IS) projects in general may not be transferrable to the context of AI. Therefore, the objective of our research has been to identify factors that can lead to AI project failure. Based on interviews with AI experts, this article identifies and discusses 12 factors that can lead to project failure. The factors can be further classified into five categories: unrealistic expectations, use case related issues, organizational constraints, lack of key resources, and technological issues. This research contributes to knowledge by providing new empirical data and synthesizing the results with related findings from prior studies. Our results have important managerial implications for firms that aim to adopt AI by helping the organizations to anticipate and actively manage risks in order to increase the chances of project success. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Failure factors of AI projects: results from expert interviewsAIartificial intelligencemachine learningMLfailuresuccessIn the last few years, business firms have substantially invested into the artificial intelligence (AI) technology. However, according to several studies, a significant percentage of AI projects fail or do not deliver business value. Due to the specific characteristics of AI projects, the existing body of knowledge about success and failure of information systems (IS) projects in general may not be transferrable to the context of AI. Therefore, the objective of our research has been to identify factors that can lead to AI project failure. Based on interviews with AI experts, this article identifies and discusses 12 factors that can lead to project failure. The factors can be further classified into five categories: unrealistic expectations, use case related issues, organizational constraints, lack of key resources, and technological issues. This research contributes to knowledge by providing new empirical data and synthesizing the results with related findings from prior studies. Our results have important managerial implications for firms that aim to adopt AI by helping the organizations to anticipate and actively manage risks in order to increase the chances of project success.UMinho Editora2023-10-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.12821/ijispm110302https://doi.org/10.12821/ijispm110302International Journal of Information Systems and Project Management; Vol. 11 N.º 3 (2023); 25-40International Journal of Information Systems and Project Management; Vol. 11 No. 3 (2023); 25-402182-7788reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://revistas.uminho.pt/index.php/ijispm/article/view/5358https://revistas.uminho.pt/index.php/ijispm/article/view/5358/5907Schlegel, DennisSchuler, KajetanWestenberger, Jensinfo:eu-repo/semantics/openAccess2023-12-09T09:30:19Zoai:journals.uminho.pt:article/5358Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:33:48.012148Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Failure factors of AI projects: results from expert interviews |
title |
Failure factors of AI projects: results from expert interviews |
spellingShingle |
Failure factors of AI projects: results from expert interviews Schlegel, Dennis AI artificial intelligence machine learning ML failure success |
title_short |
Failure factors of AI projects: results from expert interviews |
title_full |
Failure factors of AI projects: results from expert interviews |
title_fullStr |
Failure factors of AI projects: results from expert interviews |
title_full_unstemmed |
Failure factors of AI projects: results from expert interviews |
title_sort |
Failure factors of AI projects: results from expert interviews |
author |
Schlegel, Dennis |
author_facet |
Schlegel, Dennis Schuler, Kajetan Westenberger, Jens |
author_role |
author |
author2 |
Schuler, Kajetan Westenberger, Jens |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Schlegel, Dennis Schuler, Kajetan Westenberger, Jens |
dc.subject.por.fl_str_mv |
AI artificial intelligence machine learning ML failure success |
topic |
AI artificial intelligence machine learning ML failure success |
description |
In the last few years, business firms have substantially invested into the artificial intelligence (AI) technology. However, according to several studies, a significant percentage of AI projects fail or do not deliver business value. Due to the specific characteristics of AI projects, the existing body of knowledge about success and failure of information systems (IS) projects in general may not be transferrable to the context of AI. Therefore, the objective of our research has been to identify factors that can lead to AI project failure. Based on interviews with AI experts, this article identifies and discusses 12 factors that can lead to project failure. The factors can be further classified into five categories: unrealistic expectations, use case related issues, organizational constraints, lack of key resources, and technological issues. This research contributes to knowledge by providing new empirical data and synthesizing the results with related findings from prior studies. Our results have important managerial implications for firms that aim to adopt AI by helping the organizations to anticipate and actively manage risks in order to increase the chances of project success. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-10-04 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.12821/ijispm110302 https://doi.org/10.12821/ijispm110302 |
url |
https://doi.org/10.12821/ijispm110302 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.uminho.pt/index.php/ijispm/article/view/5358 https://revistas.uminho.pt/index.php/ijispm/article/view/5358/5907 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
UMinho Editora |
publisher.none.fl_str_mv |
UMinho Editora |
dc.source.none.fl_str_mv |
International Journal of Information Systems and Project Management; Vol. 11 N.º 3 (2023); 25-40 International Journal of Information Systems and Project Management; Vol. 11 No. 3 (2023); 25-40 2182-7788 reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133603802644480 |