Paper Number
ECIS2026-2625
Paper Type
CRP
Abstract
Post-merger IS integration often threatens the human-centered and IT-embedded knowledge of acquired firms. Drawing on the knowledge-based view of the firm and a technology affordance lens, we examine two consecutive acquisitions of the same digital M&A target to explain how an emerging technology reshapes IS integration choices. While the first acquirer pursued a disruptive "rip-and-replace" strategy for the target’s proprietary ERP system, the second adopted a "retain-and-revive" approach, enabled by newly discovered GenAI affordances. In particular, LLM-supported affordances like learning system knowledge through chat increased knowledge transferability, knowledge aggregation, and efficiency; reducing prior assumptions about system intransparency, personnel dependence, and conversion costs. Our findings show how GenAI reconfigures perceived knowledge challenges, alters integration logics, and expands feasible paths for value capture. The study contributes to M&A and IS integration literature by revealing how affordance actualization can shift strategic choices between the replacement and retainment of target systems.
Recommended Citation
Erber, Lena; Ortiz de Guinea, Ana; and Steininger, Dennis M., "From Knowledge Loss To Knowledge Leverage: How Gen AI Affordances Transform Post-Merger IS Integration" (2026). ECIS 2026 Proceedings. 24.
https://aisel.aisnet.org/ecis2026/is_adopt/is_adopt/24
From Knowledge Loss To Knowledge Leverage: How Gen AI Affordances Transform Post-Merger IS Integration
Post-merger IS integration often threatens the human-centered and IT-embedded knowledge of acquired firms. Drawing on the knowledge-based view of the firm and a technology affordance lens, we examine two consecutive acquisitions of the same digital M&A target to explain how an emerging technology reshapes IS integration choices. While the first acquirer pursued a disruptive "rip-and-replace" strategy for the target’s proprietary ERP system, the second adopted a "retain-and-revive" approach, enabled by newly discovered GenAI affordances. In particular, LLM-supported affordances like learning system knowledge through chat increased knowledge transferability, knowledge aggregation, and efficiency; reducing prior assumptions about system intransparency, personnel dependence, and conversion costs. Our findings show how GenAI reconfigures perceived knowledge challenges, alters integration logics, and expands feasible paths for value capture. The study contributes to M&A and IS integration literature by revealing how affordance actualization can shift strategic choices between the replacement and retainment of target systems.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.