User Knowledge Innovation of AI - powered Products: The Mechanism of How Enterprise Knowledge Solicitation and Folk Cognition Interaction Impact on AI Products' Fitness with the User's Mental Model of Need through Knowledge Integration
Wu Bo, Biaoxin Chen · 2025
Unlike traditional products that aim to meet users' functional needs, AI product innovation requires a deeper exploration of users' latent future needs. Since most of these needs are not immediately apparent to users and cannot be easily articulated as explicit knowledge, observing users' life scenarios, gathering and synthesizing relevant information into explicit knowledge is crucial for aligning with users' mental models of needs. This study explores how traditional corporate knowledge - gathering and public cognitive - interaction activities enhance the alignment between AI products and users' mental models of needs. These activities involve collecting users' knowledge, experience, and scenario - based information. The results show the paths in which these activities contribute to this alignment. While corporate knowledge - gathering is effective for knowledge and experience, it has limited impact on scenario - information collection. Public cognitive - interaction, on the other hand, promotes the absorption of all three types of knowledge, and their combined efforts ultimately enhance the alignment with users' mental models of needs.