Paper Type
Complete
Abstract
The implementation of artificial intelligence (AI) presents considerable opportunities for transforming business operations, while also posing significant challenges, particularly in organizational, process-related, and technological dimensions (Merhi, 2021, 2023). A structured framework is thus essential for effective implementation. Drawing on 25 qualitative interviews, this study builds on Merhi’s (2021, 2023) AI implementation process model to reassess its practical applicability and identify areas for refinement. By integrating change management elements across the pre-implementation, implementation, and post-implementation phases, we propose a more dynamic and adaptable framework. This holistic approach emphasizes the centrality of organizational change management, extending the original model as well as offering practical insights and new success factors that align with current developments in AI adoption.
Paper Number
2231
Recommended Citation
Baumann, Carolin; Peters, Leonore Dorothea Katharina; and Schein, Lisa-Maria, "Ready for IT? AI Implementation in the Transformation Era" (2025). AMCIS 2025 Proceedings. 18.
https://aisel.aisnet.org/amcis2025/sig_odis/sig_odis/18
Ready for IT? AI Implementation in the Transformation Era
The implementation of artificial intelligence (AI) presents considerable opportunities for transforming business operations, while also posing significant challenges, particularly in organizational, process-related, and technological dimensions (Merhi, 2021, 2023). A structured framework is thus essential for effective implementation. Drawing on 25 qualitative interviews, this study builds on Merhi’s (2021, 2023) AI implementation process model to reassess its practical applicability and identify areas for refinement. By integrating change management elements across the pre-implementation, implementation, and post-implementation phases, we propose a more dynamic and adaptable framework. This holistic approach emphasizes the centrality of organizational change management, extending the original model as well as offering practical insights and new success factors that align with current developments in AI adoption.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIGODIS