AI in Mentoring and Duplication for Network Marketing: A Systematic Literature Review using TPACK and ANT - Sitinjak, Manuntun; Irawan, gustinus Purna; Handoyo, Sarwo Edy (Asian Journal of Management Analytics, 2025)
Mentoring and duplication are key components of member development in multi-level marketing (MLM), yet traditional approaches often struggle with scalability, consistency, and personalization. This study systematically reviews the integration of Artificial Intelligence (AI) into MLM mentoring and duplication using the Technological Pedagogical Content Knowledge (TPACK) and Actor-Network Theory (ANT) frameworks. A Systematic Literature Review (SLR) was conducted following the PRISMA protocol, analyzing 60 peer-reviewed articles published between 2020 and 2025 from Scopus, ScienceDirect, and Google Scholar. Results indicate that AI enhances mentoring through personalized support, real-time feedback, and adaptive learning, while improving duplication via automated training, communication, and workflow replication. The synthesis reveals that combining TPACK and ANT provides a comprehensive lens to understand how digital tools interact with human actors and knowledge networks.