Urban underground environment is an intricate maze of utility lines and highly unpredictable geological conditions, making efficient space utilization a challenge. While the direct investigation techniques offer accuracy, their time-intensive and intrusive nature limits applicability in congested cityscapes. Nondestructive geophysical tools like ground-penetrating radar (GPR) has gained prominence for utility detection and subsurface characterization. However, GPR still faces persistent challenges affecting data quality, interpretability and overall survey reliability. This study aims to systematically identify, categorize and address the key challenges of implementing GPR for underground utility detection and subsurface profiling and develop a challenge-solution framework. Drawing on the comprehensive systematic literature review (spanning 2000–2024), bibliometric and scientometric analysis and firsthand observations from site visits to underground pipeline and metro projects, this study identifies fifty-one specific challenges, such as signal attenuation in clay-rich soils, clutter from overlapping utilities, productivity and workflow inefficiencies. These are synthesized into nine overarching categories—pertaining to technical limitations, data analysis issues, antenna-specific problems and more. Further, corresponding mitigation strategies and possible solutions are organized under seven actionable themes and a structured challenge-solution framework is developed, supporting practical implementation. The study concludes with a forward-looking roadmap, emphasizing the potential developments like multi-sensor fusion, machine learning algorithms, IoT integration and strategic trade-offs, to offer a holistic perspective to the researchers working to improve underground space diagnostics and planning.