The vendor required to provide artificial intelligence (AI) for planning applications can enhance the streamlining of workflows, automate routine tasks, improve regulatory compliance, enable data-informed decision-making, and enhance opportunities to support long-term planning and public engagement processes, all of which contribute to a more responsive and transparent planning process.
- By integrating AI into these core functions, the city intends to create a more efficient, responsive, and future-ready planning system including but not limited to:
1. Application review and pre-screening:
• Streamlining drawing and document analysis and compliance checks, automating pre-screening tasks to reduce processing times while ensuring accuracy and policy adherence.
• Helps applicants understand the planning process and provides instant compliance feedback on responses.
2. Data-driven decision-making:
• Using analytics for scenario modelling and GIS integration to empower data-driven insights, enabling planners to anticipate impacts and evaluate development options effectively.
3. Workflow optimization:
• Automating routine tasks such as data entry and offering real-time tracking to enhance process efficiency, reduce circulation distribution times, and provide applicant transparency.
4. Improved stakeholder collaboration:
• With the right tools and data, AI and automation can enhance spatial analysis and visualization opportunities to better inform the public, facilitate long-term urban planning by analyzing growth patterns and forecasting needs.
• IT can also enhance compliance and risk management and support sustainable urban growth.
5. Improved service delivery:
• Use of AI technology to create smarter, faster, cost-effective and high-quality services.
• This can increase value-added work, provide opportunities to improve services based on data and trends collected, provide better modelling analysis, and improve financial management.
6. Enhanced transparency:
• The improved processes will strengthen transparency by enabling applicants to track the status of their responses, identify potential areas of improvement, and gain clarity on requirements.
• This fosters a more open and predictable planning experience.
- The city is particularly interested in gaining insight and information on solutions that address the following functional areas:
1. Application intake and validation
• Intelligent document recognition and data extraction from submitted materials
• Automated completeness checks and validation against submission requirements to reduce manual review and improve first-time submission quality
2. Policy and regulation compliance
• Natural language processing (NLP) tools to apply zoning bylaws and official plan policies
• AI-driven rule engines to assist with the assessment of applications for compliance with municipal and provincial regulations such as the act and the code.
3. Decision support and analysis
• Analytics for application outcomes, approval timelines, and identify potential risks
• Machine learning models to analyze historical data, detect trends, and support proactive planning decisions
4. Visualization and public engagement
• AI-enhanced modeling and scenario planning tools to support public consultation and stakeholder engagement
• Chatbots or virtual assistants to provide applicants and the public with real-time guidance and information
5. Workflow optimization
• AI based task routing and workload balancing to improve internal coordination and reduce circulation times
• Integration with existing planning systems, permitting platforms, and GIS tools to ensure seamless data flow and operational efficiency.
- Critical use cases
• Automated application document review and validation - AI tools automatically analyze submitted documents (e.g., site plans, reports, drawings, forms) to verify completeness, identify missing elements, and ensure alignment with submission requirements.
• Automated zoning and official plan policy compliance checks - natural language processing (NLP) engines define information from the zoning bylaws, official plans, and building codes to assess whether applications meet regulatory requirements.
• Automated building code review - AI systems analyze building plans to check for compliance with the code.
• Analytics for application outcomes - machine learning models that analyze historical data, approval timelines, identify high-risk applications, and forecast potential issues.
• Intelligent workflow routing - AI classifies building applications by complexity and routes them to appropriate reviewers or departments based on expertise and workload.
• Conversational AI for applicant support - AI-powered chatbots provide real-time assistance to applicants, answering questions, guiding them through submission steps, and offering status updates.
• AI enhanced public engagement tools - AI integrates with interactive visualizations (e.g., 3d models, GIS maps scenario simulations) of proposed developments to support public consultation and feedback.
• Data driven insights for strategic planning - AI analyzes trends in application types, geographic distribution, and approval rates to inform policy development and long-term planning.
• AI-assisted growth forecasting - AI models generate localized population and employment forecasts by analyzing development activity, economic and demographic trends, and incorporating official plan land use policies and zoning by-law considerations to support long-term planning over a 30-year horizon.
- Questions/Inquires Deadline: April 28, 2026
