Advancing Fit-for-Purpose Access to CII Best Practices Using Multimodal Large Language Models

Abstract

The Construction Industry Institute (CII) has conducted extensive research over the past four decades, culminating in the identification of 17 best practices (BPs) proven to enhance overall project success when effectively implemented. However, the BPs remains underutilized in the construction industry due to the vastness of the related knowledgebase, heterogeneous data formats, and time-intensive nature of interpretation. This research addresses these challenges by developing a new CII BP handbook and an artificial intelligence (AI) tool designed to improve CII knowledge accessibility and usability for member companies. The first tool, BP Primer , was developed using a hybrid approach that combines qualitative analysis with retrieval-augmented generation (RAG)–based question and +answering. It extracts actionable insights (termed as “golden nuggets”) from 54 CII research reports and organizes them across the 17 BPs and project lifecycle phases, enabling users to quickly locate strategies tailored to their specific needs. Additional features include BP-level and report-level executive summaries and frequently asked questions (FAQs) to support high-level CII BP comprehension. The second tool, a BP Conversational AI , is built on a multimodal RAG framework, allowing users to interact with the BP multimodal knowledge base through natural language queries and document-grounded responses. Both tools were piloted with industry partners, and key lessons learned from the implementation have been documented. This research establishes a foundation for applying multimodal large language model (MLLM)-driven frameworks to construction knowledge curation. The curated knowledge can effectively guide construction professionals toward fit-for-purpose insights that support informed decision-making.