Integrating <scp>AI</scp> in Construction Estimation Education: A Comparative Study of Togal <scp>AI</scp> and Bluebeam Revu 20

ABSTRACT The integration of artificial intelligence (AI) into construction education is transforming how future professionals approach estimation tasks. This study examines the role of Togal AI—an AI‐powered estimation tool—alongside the industry‐preferred Bluebeam Revu 20 in undergraduate construction education. Through a structured experiment with 60 students, we tracked flooring area estimations for a school building, collecting both quantitative performance metrics and qualitative survey responses. Key findings show Togal AI accelerated task completion by 51.3%, improved measurement accuracy by 20.4%, enhanced team coordination by 28.4% and sped up change order processing by 75.7%, while boosting confidence by 55.2%. However, semi‐structured interviews revealed concerns that over‐reliance on automation might hinder critical thinking. This highlights the importance of curricular frameworks positioning AI as an educational support tool rather than a replacement for essential competencies. This study offers practical strategies for integrating AI tools into estimation education. While Togal AI automates measurement, freeing cognitive capacity for large, complex projects, its technical limitations, oversimplified markups and risk of over‐reliance on AI underscore the need for curricula that balance AI efficiency with manual estimation skills. These findings inform the modernization of academic curricula, ensuring AI enhances rather than replaces essential competencies in construction education.