ABSTRACT
Building permitting is an essential regulatory process aiming to ensure that new construction meets various safety, zoning, and environmental standards. Unfortunately, the process is cumbersome, slow, and labor-intensive. With the major opportunities that Artificial Intelligence (AI) introduced to the Architecture, Engineering, and Construction industry over the last years, developing AI-based solutions for the permitting process is determined to be a promising next step. This chapter explores three AI-driven approaches for transforming the permitting process: the phased approach, the one-shot approach, and the hybrid approach. In the phased approach, AI is applied across individual stages, such as application, document review, compliance checking, etc. For each process step, we discuss the potential AI applications, data requirements, sources, and possible strengths and weaknesses. In contrast, the one-shot approach seeks to produce a single AI-driven decision, evaluating the entire application at once. This latter model raises unique considerations around subjectivity, flexibility, and trust in the results, as a one-shot decision model may reduce transparency and explainability in its quest for speed. We examine the trade-offs between these major approaches, providing insights into how AI can optimize building permitting processes while addressing the challenges of automation.
