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Failure of AI projects: understanding the critical factors

  • Adoption of artificial intelligence (AI) has risen sharply in recent years but many firms are not successful in realising the expected benefits or even terminate projects before completion. While there are a number of previous studies that highlight challenges in AI projects, critical factors that lead to project failure are mostly unknown. The aim of this study is therefore to identify distinct factors that are critical for failure of AI projects. To address this, interviews with experts in the field of AI from different industries are conducted and the results are analyzed using qualitative analysis methods. The results show that both, organizational and technological issues can cause project failure. Our study contributes to knowledge by reviewing previously identified challenges in terms of their criticality for project failure based on new empirical data, as well as, by identifying previously unknown factors.

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Metadaten
Author of HS ReutlingenWestenberger, Jens; Schlegel, Dennis
URN:urn:nbn:de:bsz:rt2-opus4-35562
DOI:https://doi.org/10.1016/j.procs.2021.11.074
Erschienen in:Procedia computer science
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Article
Language:English
Year of Publication:2022
Tag:AI; artificial intelligence; failure factors; project failure; readiness; success factors
Volume:196
Issue:CENTERIS - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2021
Page Number:8
First Page:69
Last Page:76
DDC classes:004 Informatik
Open Access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International