Paper Number
ECIS2025-1038
Paper Type
CRP
Abstract
A unique and extensive internal knowledge base is essential for organizations to remain competitive. However, the departure of employees, for example, due to retirement, poses a risk of knowledge loss. Artificial Intelligence (AI) aims to offer a solution by supporting knowledge sharing before and after employees exit, but research on knowledge sharing through AI related to the departure of employees is limited. To explore the effective use of AI for knowledge sharing in organizations, we conducted a qualitative study using a triangulation approach. Data collection followed a two-stage design: expert interviews provided foundational insights, followed by focus group discussions to further evaluate and validate findings. We identified key factors related to the nature of knowledge, motivation and opportunities for knowledge sharing, and workplace culture. Our findings support research on integrating AI into knowledge-sharing systems, highlighting the importance of considering workplace culture to create meaningful and valuable uses of technology.
Recommended Citation
Schaetzle, Anna, "Sharing Is Caring: Exploring AI-Based Knowledge Sharing Within Work Environment Culture" (2025). ECIS 2025 Proceedings. 6.
https://aisel.aisnet.org/ecis2025/bpm/bpm/6
Sharing Is Caring: Exploring AI-Based Knowledge Sharing Within Work Environment Culture
A unique and extensive internal knowledge base is essential for organizations to remain competitive. However, the departure of employees, for example, due to retirement, poses a risk of knowledge loss. Artificial Intelligence (AI) aims to offer a solution by supporting knowledge sharing before and after employees exit, but research on knowledge sharing through AI related to the departure of employees is limited. To explore the effective use of AI for knowledge sharing in organizations, we conducted a qualitative study using a triangulation approach. Data collection followed a two-stage design: expert interviews provided foundational insights, followed by focus group discussions to further evaluate and validate findings. We identified key factors related to the nature of knowledge, motivation and opportunities for knowledge sharing, and workplace culture. Our findings support research on integrating AI into knowledge-sharing systems, highlighting the importance of considering workplace culture to create meaningful and valuable uses of technology.
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