Cities are increasingly adopting artificial intelligence to tackle delays in housing permitting caused by incomplete applications. AI technologies can efficiently scan and flag errors, reducing the need for multiple revisions. This initiative is part of a broader push supported by two new federal funding streams: the Innovation Fund, with $200 million annually, and grants from the U.S. Department of Housing and Urban Development for automated building code systems.
Syracuse, NY, has applied for a HUD grant alongside other cities like Coeur d’Alene, ID, and Mobile, AL. Vincent Scipione, Syracuse’s Chief Information Officer, emphasized the importance of data governance and algorithm design in the competitive bidding process for AI systems. These systems aim to assist developers in submitting complete applications, minimizing revision timelines.
Major cities such as Baltimore and Los Angeles have already implemented AI tools for housing permits, while smaller cities like Everett, WA, are following suit. In Texas, Harris County allocated $750,000 to accelerate permit processing through AI. The Denver City Council approved a $4.6 million contract for an AI Guided Plan Review tool, aiming to increase first-round application acceptance from 37% to 80%.
Louisville, KY, is piloting an AI-assisted system to cut delays from incomplete submissions. This system uses property data and GIS to identify missing information, potentially reducing resubmissions by over 50%. Despite such advancements, concerns persist. Seattle, for instance, reported CivCheck’s 87% accuracy but hesitated on full adoption pending further funding and support.
CivCheck
Honolulu pioneered AI permitting with CivCheck, which checks applications against local codes, guiding corrections and reducing review cycles. However, its rollout faced employee backlash, with calls for a return to the previous system. Despite this, CivCheck has significantly cut review times and correction cycles, with notable improvements in permit processing times.
Seattle’s pilot of CivCheck demonstrated a 50% reduction in average review days, yet the city remains cautious about full implementation. CivCheck works with over 20 cities, enhancing permit turnaround times by reducing feedback cycles.
A two-way street
AI’s role in planning extends beyond technical tasks, offering planners more time for public engagement and community-focused initiatives. However, AI cannot replicate human judgment in complex zoning scenarios. The permitting process remains a collaborative effort between cities and developers, with AI offering guidance to applicants unfamiliar with the system.
Despite AI’s potential to streamline processes, city officials remind applicants of their role in preventing delays. Effective guidance and validation from cities can mitigate common application errors, ensuring smoother permitting experiences.
