A Strategic Framework for Transforming the Construction Industry via Large Language Models

Abstract

Although the broader construction sector is experiencing rapid digital growth, specific domains, such as construction’s organizational operations, still rely on manual workflows, leading to operational inefficiencies, communication gaps, and delayed project timelines. To address these challenges, this study develops an applied strategic framework for integrating Large Language Models (LLMs), such as ChatGPT, Google’s Gemini, and DeepSeek AI, to revolutionize core organizational operations. Using McKinsey’s 7S framework for organizational diagnosis, the research identified critical performance gaps in document management, interdepartmental communication and on-site decision-making. To bridge these gaps, the proposed framework established five key LLM-driven initiatives. Key findings indicate that the strategic implementation of these AI tools can reduce document preparation time by up to 50% and lower operational rework costs by at least 25%. Furthermore, the study formulated targeted Key Performance Indicators (KPIs) and a comprehensive risk mitigation strategy. The risk assessment highlights that strict data encryption protocols and mandatory human-in-the-loop validation are essential to counteract potential AI inaccuracies and successfully overcome employee resistance to change. Ultimately, this evidence-based framework equips infrastructure providers with the strategies needed to successfully transition from traditional, manual workflows to smart, AI-driven, highly productive operations.