Greater Sudbury city council has given the green light to an $800,000 pilot project utilizing artificial intelligence (AI) to enhance the review of building permit applications. The objective is to identify issues earlier in the process and reduce processing times without replacing city staff.
The AI technology will serve as an initial screening tool when applicants submit plans through the city’s Pronto portal. It will check for missing information and potential violations of Greater Sudbury’s zoning bylaw and sections of the Ontario Building Code. This automated review process is expected to provide feedback promptly, eliminating the need for applicants to wait days for manual reviews to identify deficiencies.
Kris Longston, the city’s general manager of planning and growth, explained that the AI system will undergo training on the city’s zoning regulations and permit procedures before becoming fully operational. Longston likened this training phase to onboarding a new employee who must grasp the system’s workings before handling complex tasks.
The CEO of the Northern Ontario Home Builders Association, Morgan Roleau, expressed cautious interest in Sudbury’s AI initiative, noting that permit delays have posed challenges for builders in the region. Roleau highlighted the potential of AI to standardize requirements and compliance checks but warned that faster screening may not address all issues within the permitting process.
Experts such as Mojgan Jadidi, an associate professor at York University, emphasized that AI can streamline repetitive tasks in permitting, freeing up professionals to focus on intricate decisions. However, they stressed the importance of human oversight for cases involving nuanced interpretations or conflicting priorities.
AI is seen as beneficial for automating compliance checks on straightforward requirements like stair dimensions or door specifications. Still, it cannot replace the critical judgment of plans examiners, especially in cases requiring interpretation of complex drawings or building code nuances.
The pilot project, funded through the Building Permit Revenue Stabilization Reserve Fund, aims to assess the effectiveness of AI in enhancing the initial stages of the permitting process. If successful, the city plans to cover the annual AI licensing costs of $350,000 through building permit fees. Evaluation of the pilot results will guide the decision on full implementation in the future.