TY  - CONF
TI  - Integrating SCRUM with the last planner system: an AI-enhanced framework
C1  - Singapore, Singapore
C3  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
SP  - 1725
EP  - 1736
PY  - 2026
DO  - 10.24928/2026/0271
AU  - Lujan, Guillermo Prado
AU  - Engineer-Manriquez, Felipe
AD  - Production Manager, Project Delivery Services, The Boldt Company, San Francisco, California, USA, guillermo.prado@boldt.com, orcid.org/0000-0002-5325-1132
AD  - Project Delivery Services Director, Project Delivery Services, The Boldt Company, San Francisco, California, USA,  Nick.Loughrin@boldt.com,
ED  - Hamzeh, Farook
ED  - Poshdar, Mani
ED  - Garcia-Lopez,, Nelly P.
AB  - 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.
KW  - Last Planner System
KW  - SCRUM
KW  - Lean Construction
KW  - Integration
KW  - Artificial Intelligence
PB  - 
T2  - Proceedings of the 34th Annual Conference of the International Group for Lean Construction (IGLC 34)
DA  - 2026/06/22
CY  - Singapore, Singapore
L1  - http://iglc.net/Papers/Details/2559/pdf
L2  - http://iglc.net/Papers/Details/2559
N1  - Export Date: 19 June 2026
DB  - IGLC.net
DP  - IGLC
LA  - English
ER  -