Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
Artificial Intelligence (AI) is increasingly gaining importance for organizations due to its immense potential for value creation and growth. However, companies struggle to tap this potential, as many AI projects fail in the early stages because of lacking guidance and best practices. To shed light on how AI adoption and transformation can be approached and what challenges organizations face, we analyzed eleven organizations of varying sizes and industries. Drawn on these insights, we identify four transformation types distinguished by different AI transformation stages and journeys. Furthermore, we develop a 3D-Model to guide enterprise-wide AI change and propose concrete recommendations for action on each dimension. Our findings help practitioners navigate, manage, and (re)evaluate their AI strategy for an enterprise-wide transformation.
Recommended Citation
Uba, Chikaodi; Lewandowski, Tom; and Böhmann, Tilo, "The AI-based Transformation of Organizations: The 3D-Model for Guiding Enterprise-wide AI Change" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 2.
https://aisel.aisnet.org/hicss-56/os/practice-based_research/2
The AI-based Transformation of Organizations: The 3D-Model for Guiding Enterprise-wide AI Change
Online
Artificial Intelligence (AI) is increasingly gaining importance for organizations due to its immense potential for value creation and growth. However, companies struggle to tap this potential, as many AI projects fail in the early stages because of lacking guidance and best practices. To shed light on how AI adoption and transformation can be approached and what challenges organizations face, we analyzed eleven organizations of varying sizes and industries. Drawn on these insights, we identify four transformation types distinguished by different AI transformation stages and journeys. Furthermore, we develop a 3D-Model to guide enterprise-wide AI change and propose concrete recommendations for action on each dimension. Our findings help practitioners navigate, manage, and (re)evaluate their AI strategy for an enterprise-wide transformation.
https://aisel.aisnet.org/hicss-56/os/practice-based_research/2