Purpose This study explores how algorithmic dependence (AD), the growing reliance on AI in organizational decision-making leads to intellectual capital erosion (ICE). It introduces a novel mediating construct, knowledge authenticity conflict (KAC), defined as the psychological tension experienced when algorithmic outcomes contradict human expertise or factual reality. This research explores how excessive reliance on AI undermines the authenticity and reliability of human knowledge, thereby weakening intellectual capital. Design/methodology/approach Employing a mixed-method design within small and medium enterprises (SMEs), where human–AI interactions are more direct and emotionally salient, the study uses Grounded Theory to conceptualize KAC and quantitative analysis (n = 920 valid responses) to test theoretical correlations. The KAC scale showed high validity (S-Content validity index/Ave = 0.951; KMO = 0.872). Cognitive Dissonance Theory was used to guide the interpretation of psychological dynamics in AI-mediated decision contexts. Findings The results indicate that AD significantly predicts both KAC (β = 0.58, p 0.001) and ICE (β = 0.39, p 0.001). Tenure and AI literacy emerge as protective factors, reducing KAC intensity. Research limitations/implications This study's cross-sectional design and reliance on self-reported data limit causal inferences. The sample consists mainly of digitally connected SMEs, which may not fully represent all small businesses worldwide. Future research could use longitudinal or experimental designs and explore KAC across diverse industries and cultures. Practical implications This research offers strategies for SMEs to manage AI integration and protect intellectual capital, including promoting AI literacy, ensuring transparent algorithmic governance, and adopting human-in-the-loop decision-making. Organizations should address psychological conflicts (KAC) to prevent erosion of human and relational capital. Originality/value By introducing KAC, this research extends intellectual capital theory, emphasizing authenticity as a vital human capital component. It provides a theoretical and practical framework for managers to enhance AI literacy and ethical governance to sustain intellectual capital in digitally transforming enterprises.
Hussain et al. (Fri,) studied this question.