Electronic waste is a growing global challenge, with projections indicating a significant increase from 58 million metric tons in 2021 to an alarming 112 million metric tons by 2050 (Forti et al., 2020; Parajuly et al., 2019). This surge underscores the urgent need for circularsolutions in managing the lifecycle of electronic products. Furthermore, the current economic and marketing dynamics often make replacement seem more appealing than repair (Sonego et al., 2022; Terzioğlu et al., 2015; VandenBerge et al., 2023). Addressing this challenge requires understanding the multifaceted barriers users face, which the Repair Motivation and Barriers Model categorizes into technical, emotional, and value-related aspects of repair (Terzioğlu, 2021). This research aims to tackle these barriers by introducing an Artificial Intelligence (AI)-powered tool called AI-Fixer that provides step-by-step repair instructions, building user confidence, and enabling self-repair practices.Within the field of Circular Economy, researchers are increasingly investigating the role of emerging digital technologies in enabling circular practices (Bressanelli et al., 2018; Sherpa & Sinha, 2021). Among these, AI holds significant promise offering capabilities such as diagnostics, predictive maintenance, and real-time repair support. This study explores the feasibility of AI-Fixer in assisting users with repairing consumer electronics. It specifically investigates whether AI can assist and empower users to repair devices.