From AI Curiosity to Capability
The pressure on planning agencies to adopt AI keeps building, and most departments still don't know where to begin. This online class gives a structured place for public-sector planners to start. Over six weeks of live sessions, self-paced modules, exercises, and activities, you and a cohort of public planners will work through what AI adoption actually looks like inside a planning department: where it belongs in your workflows, what policies need to be in place before staff start using it, and how to talk about it with your peers and managers.
The challenges of implementing AI in public planning agencies are unique — and so are the opportunities. This class will help you prepare for this technology to ensure that you can deliver the highest value to the communities you serve while protecting what matters most.
Join Tom Sanchez and a cohort of planners to workshop and develop a toolkit specific to your agency:
- Agency AI readiness assessment framework
- Draft AI governance & staff usage templates
- Planning-specific AI workflow & prompt library
- Agency AI roadmap & implementation guidance
Our next cohort begins October 15. Weekly live sessions take place Wednesdays @ 10 am PT and are recorded for later viewing. Estimated commitment time is 3-4 hours per week.
6 week live class
Top AI & planning
expert-led
Community of
planners
12 AICP CM
credits
Week 0: Pre-class participant survey and assessment
All registered participants will complete an online survey approximately two weeks before the cohort begins. Aggregate findings will be shared with the cohort during Session 1 to set context and inform how the instructor adjusts emphasis throughout the series.
Survey topics
- Agency profile: jurisdiction type, population served, department size, staffing structure
- Role and responsibilities of the participant
- Self-rated familiarity with AI concepts and tools
- Current technology environment: GIS, data systems, document management, and existing software
- Any AI tools currently used or piloted by the agency
- Existing policies that touch AI: data governance, acceptable use, privacy, procurement
- Top concerns about AI adoption in your agency
- Top goals for taking this class
Week 1: What AI is, and where it fits in planning practice
Week 1 sets the foundation. The async module is a planner-friendly primer on AI: how it differs from traditional software, what generative AI actually does, and the vocabulary you'll need for the rest of the class. The live session opens the class, shares aggregate findings from the pre-class survey, and lays out why organizational readiness is the right frame for the next six weeks.
Topics this week
- How AI differs from traditional software, and why that matters for planning
- What large language models actually do, without the math
- A short history of AI in planning, from predictive analytics to generative tools
- The hype cycle and the rapid pace of change
- Core vocabulary: training data, prompt, model, inference, evaluation
- Aggregate findings from the pre-class participant survey
- Why organizational readiness comes before tools
- Exercise: keep an AI encounter log for one week and bring 2 to 3 examples to Session 2
Week 2: The five dimensions of agency AI readiness
This is the week the class gets practical. The async module introduces the five-dimension readiness framework. The live session works through the self-assessment together and what to do when a particular dimension is weak.
Topics this week
- What readiness actually looks like, and why it comes before tools
- The five dimensions: people and skills, data, technology, use cases, governance
- How agency resources, objectives, and staff background shape what readiness means
- Common readiness profiles, from "just becoming aware" to "active pilots underway"
- How to read your own agency honestly: what to look at, who to ask
- Example readiness snapshots from small rural, midsize suburban, and large urban agencies
- Capstone Part 1: your Agency AI Readiness Self-Assessment, scored across the five dimensions
Week 3: AI tools and use cases for planning work
Week 3 surveys the AI tool landscape relevant to planning and helps you connect tools to real workflows in your own agency. The async module covers tool categories, the GovTech vendor landscape, and the build vs. buy vs. wait decision. The live session is a working demo: Tom walks through 2 to 3 planning scenarios in real time, then participants try prompts on their own candidate use cases.
Topics this week
- A survey of AI tools relevant to planning: document analysis, public comment processing, mapping, generative text, and more
- Tool categories: free or consumer tools, enterprise platforms, custom-built solutions
- The GovTech vendor landscape: how to read a pitch, what to ask, what to watch out for
- Matching tools to real workflows, not the other way around
- What AI agents are and how they change what's possible
- The build vs. buy vs. wait decision framework
- Live demos and shared prompt-building with the cohort
- Capstone Part 2 (first half): identify two to three workflows in your agency that could be candidates for AI support
Week 4: Responsible adoption: ethics, bias, and accountability
The async module covers what verification really means in practice, how bias enters AI systems, and what public accountability requires when an agency decision involves AI. The live session works through real or composite scenarios where adoption risks are most acute, and asks how your agency's current review processes would need to change.
Topics this week
- Why AI outputs require verification, and what "hallucination" looks like in practice
- How bias enters AI systems: training data, model design, deployment context
- Public accountability: transparency, explainability, and the right to understand decisions that affect the public
- Privacy and security: what data should never feed an AI tool
- Equity considerations for planning decisions that affect communities
- Professional and legal liability for AI use in official documents
- A 10-question responsible adoption checklist you can apply to any tool
- Capstone Part 2 (second half): apply the checklist to your highest-priority use case
Week 5: Governance, policy, and procurement fundamentals
This week turns to the governance work most agencies need before they can responsibly adopt AI. The async module covers what an AI usage policy needs to address, with examples from real public agencies. The live session is a working policy workshop: in small groups, you'll draft real provisions using the framework template and get live feedback from Tom.
Topics this week
- Why governance comes before tools: the public interest obligation of planning agencies
- What an AI usage policy needs to address: scope, approved uses, prohibited uses, oversight, appeals
- Three real public agency AI policies, with Tom's annotations on what's working and what's missing
- Staff roles and responsibilities: who reviews AI outputs, who has final authority
- Procurement: what to look for in vendor contracts involving AI
- Building a review cycle into policy as AI continues to evolve
- Common pitfalls in public agency AI policies and how to avoid them
- Capstone Part 3: a policy gap analysis and two to three draft provisions for your agency
Week 6: Building an adoption roadmap and capstone review
Week 6 pulls the class together into a plan you can act on. The async module covers how to sequence AI adoption, prioritize for effort and impact, and build the business case for leadership. It also doubles as your dedicated capstone work session. The live session is the capstone share-out, where small groups present their work, exchange feedback, and Tom offers themes across the cohort.
Topics this week
- How to sequence AI adoption: quick wins versus foundational investments
- Effort-versus-impact prioritization for planning workflows
- What a phased roadmap looks like over 90 days, 6 months, and 12 months
- Building the business case for leadership in terms they care about
- Adoption science basics: champions, skeptics, and why most pilots fail
- Recognizing when to bring in outside help
- Capstone Part 4: a one to two page recommendations memo addressed to your supervisor or agency leadership
- Final share-out and feedback on the complete Agency AI Readiness Brief
Meet Your Instructor: Tom Sanchez
Tom Sanchez is an urban planning scholar and educator focused on technology, transportation, equity, and planning practice. He is the author of Artificial Intelligence for Urban Planning and his recent work has focused on how planning agencies can responsibly evaluate, govern, and implement emerging AI technologies in public-sector environments.
This live class draws on real planning workflows and implementation challenges facing agencies today, with an emphasis on practical adoption rather than abstract theory.
To learn more about Tom’s pioneering work in urban planning AI research, you can read his Planetizen column about AI, or take his AI for Urban Planners courses on Planetizen Courses.
Why Planning Agencies Need AI Readiness Now
AI tools are already entering planning workflows across the public sector, often before agencies have developed clear governance, internal guidance, or shared implementation practices.
Watch a short introduction to the AI Readiness for Public-Sector Planners cohort, featuring instructor Tom Sanchez, to learn how planning agencies can prepare for more responsible, coordinated, and defensible AI adoption.
Key Benefits
- Built for public-sector planning practice. Most AI training is designed for tech, marketing, or private-sector workflows. This class focuses specifically on planning agencies, public-sector responsibilities, and real planning work.
- A usable deliverable for your agency. Participants complete a four to five page Agency AI Readiness Brief covering a scored readiness assessment, draft policy framework, and phased adoption roadmap. It is built to be shared with a director or leadership group on the day the class ends.
- A defensible framework for an unsettled question. The five-dimension readiness model (people, data, technology, governance, use cases) gives agencies a structured way to answer "what is our plan for AI?" with something more substantive than enthusiasm or avoidance.
- Internal capability, not external dependency. Staff who complete the class can lead readiness assessments, draft policy revisions, and update roadmaps as the technology evolves, without recurring outside engagements.
- AICP CM credits applied. The class is accredited for AICP Certification Maintenance credits, counting toward credential maintenance for participating planners.
- Curriculum tailored to the cohort. A pre-class participant survey, completed two weeks before the cohort begins, informs how the instructor sets emphasis, examples, and breakout groupings. The class meets cohorts where they actually are.
- Designed for early-stage adopters. No coding or data science background is required. The class is built specifically for agencies in the early stages of AI adoption, including those just becoming aware of the technology.
- Practical content grounded in planning workflows. Tools, use cases, and case studies are drawn from public planning practice. Generic AI examples are not used where planning-specific ones exist.
- Live instruction from a recognized expert. Six 90-minute live sessions with Thomas W. Sanchez, PhD, AICP, alongside self-paced async modules. Live sessions are recorded for participants who need to attend asynchronously.
- Team enrollment options. Enroll your team with single-invoice procurement. When a team participates together, individual capstones consolidate into a department-level readiness brief. Learn more about team enrollment here.
Do I need technical skills to take this class?
No. The class is designed specifically for non-technical planners, planning managers, GIS/data staff, and public-sector professionals, not software engineers or data scientists. No coding or technical background is required.
Is this course focused on ChatGPT?
No. The class explores a range of AI tools, workflows, governance considerations, and implementation strategies relevant to planning practice across the broad spectrum of tools your team may wish to adopt - not just a single platform.
What will participants leave the course with?
Participants will leave with practical organizational deliverables, including an AI readiness assessment framework, draft governance and staff usage templates, planning-specific AI workflows, and an Agency AI Readiness Brief designed to bring back to leadership for rapid implementation.
Is this class designed for agencies that are just getting started with AI?
Can planning departments enroll full teams?
Yes. Team enrollment options are available for planning departments and agencies interested in building shared readiness, governance alignment, and implementation strategies across staff teams. Contact us.
How much time should participants expect each week?
Participants should expect approximately 3-4 hours of engagement per week across live sessions, video lessons, exercises, and activities. Live sessions will also be recorded for participants who occasionally need asynchronous access.
What happens if I miss a live session?
Live sessions will be recorded and made available to enrolled participants. However, attending live is strongly encouraged to support discussion, collaboration, and cohort participation.
Does the class offer AICP CM credit?
Yes. AICP CM credits are being applied for and will be available upon successful completion of the class.
Who should attend from our agency?
The strongest class participation often includes a mix of planning leadership, planners, GIS/data staff, innovation staff, and team members involved in technology adoption or organizational policy.
When is the course offered?
The class will be offered throughout the year, currently planned for Summer, Fall, and Winter cohorts.
Still need help?
Please email us at [email protected].
Reviews
Tom and the Planetizen team delivered a super informative and well-structured course that was both practical and engaging. Tom brought years of academic research and real-world expertise to this rapidly evolving subject area and the peer discussions added valuable perspectives from across the profession. Over 6 weeks, I gained a deeper understanding of the promise and perils of AI in Planning as well as practical tools and frameworks for responsible deployment. I finished the course feeling better equipped to lead and support AI-related planning initiatives in my organization.
-Andrew M., Director, Strategic Planning & Policy
I really appreciated how the content was tailored for a planning audience, with modules and assignments building on each other to reinforce the concepts and learning. It was very practical that the weekly assignments collectively contributed toward a final course deliverable that I can actually use to help guide my team and organization to use AI in ways that are appropriate and well considered.
-Rex H., Manager, Streets Planning
Great class - thanks for offering it and laying it out so thoughtfully! The readiness score and the equity considerations were especially helpful to flag for consideration. The use case examples to work through were also helpful to frame organizational approaches and options for AI use.
- Kim M., Community Planner