Paper Number
ECIS2025-1587
Paper Type
CRP
Abstract
This study investigates the transitional phase of established enterprise platforms into the next stage of their evolution, driven by the integration of Generative AI (GenAI). Due to its inherent benefits and risks, the integration of GenAI presents several challenges that necessitate significant adaptations in platform architecture and governance. Using assemblage theory and building on empirical data from the Salesforce case, we explore how these challenges destabilize enterprise platforms and require coordinated adjustments in their architecture-governance configuration. We conceptualize this configuration as a unified, dynamic assemblage and demonstrate how aligned adjustments can restore stability and enable the emergence of new platform properties. Our findings extend digital platform literature by theorizing the transformational impact of GenAI on enterprise platforms. We highlight how these adjustments drive the evolution of platforms, generating novel properties that enhance their value and utility for customers.
Recommended Citation
Safaei, Dorsa and Haki, Kazem, "GENERATIVE AI AND THE TRANSITION OF ENTERPRISE PLATFORMS: ARCHITECTURE-GOVERNANCE ASSEMBLAGE ADJUSTMENTS" (2025). ECIS 2025 Proceedings. 7.
https://aisel.aisnet.org/ecis2025/gov_platform/gov_platform/7
GENERATIVE AI AND THE TRANSITION OF ENTERPRISE PLATFORMS: ARCHITECTURE-GOVERNANCE ASSEMBLAGE ADJUSTMENTS
This study investigates the transitional phase of established enterprise platforms into the next stage of their evolution, driven by the integration of Generative AI (GenAI). Due to its inherent benefits and risks, the integration of GenAI presents several challenges that necessitate significant adaptations in platform architecture and governance. Using assemblage theory and building on empirical data from the Salesforce case, we explore how these challenges destabilize enterprise platforms and require coordinated adjustments in their architecture-governance configuration. We conceptualize this configuration as a unified, dynamic assemblage and demonstrate how aligned adjustments can restore stability and enable the emergence of new platform properties. Our findings extend digital platform literature by theorizing the transformational impact of GenAI on enterprise platforms. We highlight how these adjustments drive the evolution of platforms, generating novel properties that enhance their value and utility for customers.
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