Paper Type
ERF
Abstract
This paper develops a theory-driven model for the post-adoption of enterprise AI, focusing on how organizations realize business value after deploying tools such as Microsoft Copilot. Rather than examining initial adoption, the paper addresses the post-adoption challenge of converting access into sustained usage, workflow integration, and measurable value. Drawing on Task-Technology Fit (TTF) and Unified Theory of Acceptance and Use of Technology (UTAUT), the model argues that feature-to-value translation and use-case discovery quality improve task-technology fit, which in turn increases business value realization. It further proposes that change enablement quality and ecosystem embeddedness strengthen facilitating conditions, thereby supporting post-adoptive use growth. The paper also situates enterprise AI use within broader platform ecosystems, especially Microsoft 365, where integration, governance, and workflow context shape perceived fit. The study contributes a conceptual foundation for future empirical research and outlines future work to develop a survey instrument for primary data collection.
Paper Number
1606
Recommended Citation
Ning, Xue; Yu, Yixiu; and Ning, Weihong, "Adopted, then What? Post-Adoption Business Value Realization in Enterprise AI" (2026). AMCIS 2026 Proceedings. 15.
https://aisel.aisnet.org/amcis2026/sigadit/sigadit/15
Adopted, then What? Post-Adoption Business Value Realization in Enterprise AI
This paper develops a theory-driven model for the post-adoption of enterprise AI, focusing on how organizations realize business value after deploying tools such as Microsoft Copilot. Rather than examining initial adoption, the paper addresses the post-adoption challenge of converting access into sustained usage, workflow integration, and measurable value. Drawing on Task-Technology Fit (TTF) and Unified Theory of Acceptance and Use of Technology (UTAUT), the model argues that feature-to-value translation and use-case discovery quality improve task-technology fit, which in turn increases business value realization. It further proposes that change enablement quality and ecosystem embeddedness strengthen facilitating conditions, thereby supporting post-adoptive use growth. The paper also situates enterprise AI use within broader platform ecosystems, especially Microsoft 365, where integration, governance, and workflow context shape perceived fit. The study contributes a conceptual foundation for future empirical research and outlines future work to develop a survey instrument for primary data collection.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIG ADIT