<p>The promise of Augmented Reality (AR) in urban regeneration remains unrealized. While immersive visualization enhances decision-making precision, its struggle to integrate technical rationality with social embeddedness persists. This study examines the role of AR in urban regeneration decision-making through a Systematic Quantitative Literature Review of peer-reviewed articles from Scopus and Web of Science. The study emphasizes the need for high-performance computing (HPC) and real-time processing for efficiently managing complex urban datasets and facilitating time-sensitive participatory decision-making. AR applications follow a temporal trajectory—from post-regeneration visualization to predictive decision support and real-time participatory platforms. Policy instrumentality and spatial adaptability often outweigh technical specifications in shaping success. Yet, AR’s implementation paradox remains: Its precision in modeling urban change contrasts with its weak integration into lived experiences. A semantic decision matrix repositions AR as a boundary object, bridging computational models with urban realities. Leveraging HPC enables scalable, high-fidelity simulations, reinforcing AR’s potential in urban regeneration.</p>