Knowledge flow in modern management: a decade of tech-reverse mentoring evolution

Abstract

Purpose This paper maps the thematic evolution of technology-focused reverse mentoring (2015–2025), specifically investigating the transition from “digital literacy” to “AI fluency” and identifying critical gaps regarding ethical governance. Design/methodology/approach A general bibliometric analysis was conducted using data from major academic databases. VOSviewer software was utilized to visualize keyword co-occurrence networks, identifying dominant conceptual clusters and temporal trends across the broader management and organizational development discipline. Findings The analysis reveals five distinct clusters: corporate strategy, social equity, well-being, mentoring mechanics and crisis adaption. Crucially, a “technological lag” is evident; while “digital transformation” is a central node, keywords related to “Generative AI,” “Prompt Engineering,” and “Ethics” are conspicuously absent from the core network, highlighting a disconnect between current literature and Industry 4.0 realities. Research limitations/implications The findings imply an urgent theoretical need to pivot from general “digital adoption” models to “AI competency” frameworks. Practical implications HR practitioners should transition from generic digital up skilling to “Strategic AI mentoring,” where junior employees guide leaders on ethical AI application and workflow integration. Originality/value This study uniquely quantifies the lack of AI and ethics discourse in the general body of knowledge, offering a novel roadmap for integrating Generative AI into competency-based training assessments.

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