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.
| Author of HS Reutlingen | Westenberger, Jens; Schlegel, Dennis |
|---|---|
| URN: | urn:nbn:de:bsz:rt2-opus4-35562 |
| DOI: | https://doi.org/10.1016/j.procs.2021.11.074 |
| ISSN: | 1877-0509 |
| Erschienen in: | Procedia computer science |
| Publisher: | Elsevier |
| Place of publication: | Amsterdam |
| Document Type: | Journal article |
| Language: | English |
| Publication year: | 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): |  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
