Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework

XAI adoption in construction requires a structured evaluation approach: The paper introduces a Content, Context, Process, and Outcome (CCPO) framework to help construction organizations systematically assess whether and how to implement explainable AI, addressing a gap where no such evaluation tools previously existed in this industry.

Understanding the "what, why, how, and when" is essential for responsible deployment: The framework guides organizations to clarify what XAI solutions do, why they're needed, how they'll be implemented, and when they should be applied—critical questions for ensuring AI systems serve legitimate business purposes rather than being adopted without clear justification.

XAI remains underdeveloped in construction despite significant potential impact: The paper notes that while XAI is expected to have "profound" effects on the construction industry, it has received limited attention to date, meaning construction organizations currently lack guidance on responsible AI implementation specific to their sector.

A practical reference point can help organizations realize AI benefits responsibly: By providing a conceptual framework for evaluation, the paper enables construction firms to move toward capturing XAI's business value while maintaining accountability—suggesting that structured evaluation processes are necessary to balance innovation with responsible AI governance.