Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
Recent advances in AI models and their integration in cloud service platforms like Microsoft Azure accelerate the options to develop individual AI solutions. Despite expanding technical possibilities, organizations still fail to successfully execute AI projects and sustainably integrate the solutions. Hence, it remains questionable whether existing project management frameworks cover the holistic complexity of individual AI projects and enable decision-makers to navigate the manifold challenges associated with AI projects. The present study aims to fill this research gap through a qualitative research approach. A structured literature review and 12 expert interviews examined by thematic analysis provide 54 AI project management challenges along 16 requirement clusters. These requirements are applied to evaluate twelve established AI-related project management frameworks. Seven areas for improvement were identified, relating to AI ethics, regulation, culture, evaluation, sourcing, impact, and modularity guidelines. Thus, this work serves as a fundament for designing novel AI project management artifacts.
Recommended Citation
Wrobel, Lasse; Dietzmann, Christian; and Alt, Rainer, "Ready for Managing AI Projects? An Analysis of AI Project Management Frameworks" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 9.
https://aisel.aisnet.org/hicss-58/os/ai_and_organizing/9
Ready for Managing AI Projects? An Analysis of AI Project Management Frameworks
Hilton Waikoloa Village, Hawaii
Recent advances in AI models and their integration in cloud service platforms like Microsoft Azure accelerate the options to develop individual AI solutions. Despite expanding technical possibilities, organizations still fail to successfully execute AI projects and sustainably integrate the solutions. Hence, it remains questionable whether existing project management frameworks cover the holistic complexity of individual AI projects and enable decision-makers to navigate the manifold challenges associated with AI projects. The present study aims to fill this research gap through a qualitative research approach. A structured literature review and 12 expert interviews examined by thematic analysis provide 54 AI project management challenges along 16 requirement clusters. These requirements are applied to evaluate twelve established AI-related project management frameworks. Seven areas for improvement were identified, relating to AI ethics, regulation, culture, evaluation, sourcing, impact, and modularity guidelines. Thus, this work serves as a fundament for designing novel AI project management artifacts.
https://aisel.aisnet.org/hicss-58/os/ai_and_organizing/9