<![CDATA[The management of digital projects involving both physical infrastructure and artificial intelligence technology in government procurement environments presents significant challenges due to rigid sequential workflows and strict regulatory requirements. This research examines the integration and implementation of the Kanban method in a digital project for the procurement of an AI-based Forensic Device Communication system within a government security agency, with the objective of enhancing time efficiency in project execution. An intrinsic case study approach was employed to compare the conventional 92-day linear project model with the Kanban-based execution model. Data were collected through participant observation, document analysis, and structured field documentation across 33 strategic installation locations. The Kanban system was implemented using a digital board with six workflow columns and Work-In-Progress limits to manage parallel task execution. Source triangulation through digital Kanban records, official completion reports, and field observations ensured data validity. The Kanban method reduced project duration from 92 days to 49 calendar days, achieving a 46% improvement in time efficiency. The pull system approach and transparent task visualization enabled early identification of administrative bottlenecks, including licensing delays and inter-team coordination issues, without compromising the technical quality of 22 new AI-based CCTV units integrated with 11 existing units. These findings demonstrate that agile visual management methodologies can be effectively adapted to complex government procurement projects while maintaining regulatory compliance. This study provides an empirical model for integrating Kanban within public sector frameworks. Future research may extend this model to multi-agency procurement contexts.]]>
