Mixed-methods study identifies facilitators and obstacles in human-AI collaboration, suggesting design improvements for knowledge audits.
This study proposes a new design for a knowledge audit, focusing on human-AI knowledge augmentation within a consulting firm’s setting. It adopts a mixed-method paradigm, including interviews, quantitative surveys and Social Network Analysis, to identify obstacles, facilitators, and AI-mediated flows within a Community of Practice. Findings show strong motivations and AI readiness coexist with poor documentation and codification. The paper reframes the audit as a design-oriented tool for mapping how human–AI collaboration shapes organisational knowledge maturity.
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Su et al. (2026) studied this question.
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