https://doi.org/10.24928/2026/0271
While both the Last Planner System (LPS) and SCRUM have demonstrated benefits independently, existing research lacks a practitioner-grounded framework that integrates these approaches across planning horizons. Grounded in a shared epistemological foundation of empiricism (where planning is continuously adjusted through feedback and learning) this study adopts an inductive, case-based approach to develop an initial framework outline. This research consists of a comparative analysis of LPS and SCRUM across six key dimensions, the synthesis of an integrated framework with AI as an augmentation layer, and an illustrative case study of a complex construction project. Results indicate that LPS provides stability through multi-horizon planning and commitment management, while SCRUM enhances short-cycle coordination, learning, and role clarity. AI further supports these processes by improving information synthesis, visibility, and anticipatory decision-making, while maintaining a human-in-the-loop approach. This study contributes a structured, practitioner-informed starting point for integrating Lean, Agile, and AI in construction, highlighting the need for further validation and development through future research.
Last Planner System, SCRUM, Lean Construction, Integration, Artificial Intelligence
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Reference in APA 7th edition format:
Lujan, G. P. & Engineer-Manriquez, F.. (2026). Integrating SCRUM with the last planner system: an AI-enhanced framework. In Hamzeh, F., Poshdar, M., & Garcia-Lopez,, N. P. (Eds.), Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34) (pp. 1725–1736). https://doi.org/10.24928/2026/0271
Shortened reference for use in IGLC papers:
Lujan, G. P. & Engineer-Manriquez, F.. (2026). Integrating SCRUM with the last planner system: an AI-enhanced framework. IGLC34. https://doi.org/10.24928/2026/0271