Exploring the collaboration between humans and AI-grounded epistemic objects to facilitate knowledge integration of “who knows what” under corporate crises

Purpose This study aims to explore how human actors collaborate with artificial intelligence (AI)-grounded epistemic objects (EOs) to facilitate knowledge integration of “who knows what” during corporate crises. Design/methodology/approach This study used a 15-month focused ethnography at an internationally renowned Chinese organization. Findings Human actors collaborate with AI-grounded EOs to facilitate knowledge integration of “who knows what” during corporate crises through connecting, eliciting, committing, converging, combining and applying across three iterative stages of specialization, credibility and coordination. Originality/value This study offers three novel advances: (1) through a 15-month focused ethnography, the authors reveal how human intelligence (HI) and AI synergize to enable knowledge integration via a three-stage mechanism involving six micro-processes, uncovering the “black box” of AI–HI collaboration. (2) The authors uniquely apply EO theory to AI-generated outputs in knowledge management–corporate crisis management contexts, demonstrating the agentic role of AI-grounded EOs in strategic knowledge synthesis, beyond its typical framing as passive “tools”. (3) The model resolves tensions in balancing algorithmic rationality with human moral judgment during high-stakes crises.

Authors

Institutions

Publication Details

Journal
Journal of Knowledge Management
Published
2025-11-06
DOI
https://doi.org/10.1108/jkm-01-2025-0058
Citations
1
Primary Topic
Management and Organizational Studies
Type
article
Field-Weighted Citation Impact
2.76
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the collaboration between humans and AI-grounded epistemic objects to facilitate knowledge integration of “who knows what” under corporate crises

Tianyu Liu, Yilin Zhu, Jiayuan Liu, Jianzhou Yan
1 citations
Journal of Knowledge Management
Management and Organizational Studies
2.76
article

Exploring the collaboration between humans and AI-grounded epistemic objects to facilitate knowledge integration of “who knows what” under corporate crises

Tianyu Liu, Yilin Zhu, Jiayuan Liu, Jianzhou Yan
article en
1 citations

Abstract

Purpose This study aims to explore how human actors collaborate with artificial intelligence (AI)-grounded epistemic objects (EOs) to facilitate knowledge integration of “who knows what” during corporate crises. Design/methodology/approach This study used a 15-month focused ethnography at an internationally renowned Chinese organization. Findings Human actors collaborate with AI-grounded EOs to facilitate knowledge integration of “who knows what” during corporate crises through connecting, eliciting, committing, converging, combining and applying across three iterative stages of specialization, credibility and coordination. Originality/value This study offers three novel advances: (1) through a 15-month focused ethnography, the authors reveal how human intelligence (HI) and AI synergize to enable knowledge integration via a three-stage mechanism involving six micro-processes, uncovering the “black box” of AI–HI collaboration. (2) The authors uniquely apply EO theory to AI-generated outputs in knowledge management–corporate crisis management contexts, demonstrating the agentic role of AI-grounded EOs in strategic knowledge synthesis, beyond its typical framing as passive “tools”. (3) The model resolves tensions in balancing algorithmic rationality with human moral judgment during high-stakes crises.

Journal of Knowledge Management
China Pharmaceutical University (CN)
Openalex Percentile: Top 7%
Management and Organizational Studies
2.76
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.