Why Generic AI Isn’t Built for Planning
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Key Points
- Generic AI is not constrained to adopted local regulations. Planning requires answers grounded in jurisdiction-specific ordinances and plans.
- Citations are essential for defensible planning guidance. Without direct links to adopted code sections, AI answers cannot be verified.
- Planning-grade AI must respect authority boundaries. Explanation and navigation are appropriate; determinations remain with staff.
Planning-Grade AI Series
This article is part of a multi-part series examining how artificial intelligence should function within municipal and county planning environments. The series explores authority boundaries, the limits of generic AI, document readiness, and governance considerations for responsible deployment. Together, these articles outline the standards required for planning-grade AI in a regulatory setting.
Artificial intelligence is increasingly used to answer questions, summarize information, and support research across many fields. In planning and zoning, however, the way information is governed and applied creates limits that general-purpose AI tools are not designed to respect.
Planning information is not generic. Zoning regulations, subdivision standards, engineering requirements, and adopted plans are jurisdiction-specific, legally binding documents. Answers must be grounded in the exact language a community has adopted, not generalized from patterns elsewhere.
This distinction matters as cities and counties consider how AI fits into planning workflows.
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Generic AI is trained to generalize, not apply adopted regulations
General-purpose AI tools are trained on large, diverse datasets drawn from public internet sources. Their purpose is to generate responses that are plausible and readable across a wide range of topics.
Planning requires a different approach. Regulatory questions depend on precise definitions, conditions, exceptions, and cross-references within a single jurisdiction’s adopted documents. When AI is optimized to generalize, it may produce answers that sound confident but are not anchored in the governing text.
In planning, confidence without authority creates risk.
Generic AI cannot reliably distinguish which local regulations govern
Zoning and development regulations vary significantly from one community to another. Even neighboring jurisdictions may use the same terms to mean very different things.
Generic AI tools do not have an inherent understanding of which ordinance applies, which version is current, or whether a provision has been amended. Without being constrained to a defined, authoritative source set, they cannot reliably distinguish between governing language and unrelated examples.
This lack of boundary awareness makes general AI unsuitable for regulatory explanation.
Generic AI cannot provide reliable, verifiable citations
Planning decisions and guidance rely on traceable citations. Staff, applicants, and the public need to know not only what a rule says, but where it appears in the adopted code or plan.
General AI tools typically paraphrase information rather than link answers directly to authoritative sections. Even when a citation is provided, it may not correspond to an adopted document or the current version in effect.
Without reliable citations, AI-generated answers cannot be verified or defended.
Generic AI blurs the line between explanation and determination
Planning workflows depend on a clear separation between explaining adopted regulations and making determinations. Regulatory guidance must be conditional and informational, not prescriptive.
Generic AI systems often present conclusions without signaling uncertainty or dependencies. This can give users the impression that an answer represents a final determination rather than a preliminary explanation.
In a planning context, that ambiguity creates confusion for applicants and additional risk for staff.
What planning-grade AI must do to work in zoning and planning
AI designed for planning must operate within defined authority boundaries. It should:
- Draw only from adopted, jurisdiction-specific documents
- Use citation-linked explanations tied to the governing text
- Signal uncertainty and dependencies clearly
- Avoid parcel-level application unless explicitly supported by verified data
- Preserve staff judgment and formal review processes
These requirements are about governance, not sophistication. The goal is reliable support for research and understanding, not automated decision-making.
Why understanding AI limits matters for cities and counties
AI use in local government is expanding, whether through formal tools or informal experimentation. Understanding the limits of generic AI helps communities avoid unintended risk and focus on approaches that align with planning practice.
For planning and zoning, responsible AI use starts with systems designed to respect adopted authority, not bypass it.
The Wrap Up
General-purpose AI tools are not built for regulatory environments; planning-grade AI must be designed around adopted authority, clear limits, and verifiable sources. To learn more about how your community can implement AI to streamline planning, zoning and ordinance research, schedule a consultation with our CEO.
Continue the Series
Previous: AI as a Planning Assistant, Not a Decision Maker
Next: Preparing Planning Documents for AI & Advanced Digital Tools
About enCodePlus – Intelligent Planning, Zoning and Codification Software
enCodePlus is a unique, web-based technology platform delivering a full suite of planning, zoning and municipal code tools and features, together with full or hybrid code management services. Created by the planning experts at Kendig Keast Collaborative, the platform serves planners and zoning administrators, clerks, attorneys, managers, economic developers, and consultant partners. The cutting-edge software streamlines the rejuvenation of the format and usefulness of plans, studies, codes and ordinances, design guidelines, standards and specifications and the processes to create and publish them.
Frequently Asked Questions
Below, we’ve compiled answers to some common inquiries about generic vs. planing-grade AI.
Why can’t cities use tools like ChatGPT for zoning questions?
General-purpose AI tools are not trained on a city’s official, approved documents, and cannot reliably cite or apply jurisdiction-specific regulations.
What makes AI “planning-grade”?
Planning-grade AI is constrained to adopted documents, uses citation-linked explanations, and clearly signals uncertainty without making determinations.
Are generic AI tools accurate for planning information?
They may appear accurate, but without authoritative sources and citations, their answers cannot be verified or defended.
Why are citations critical in planning AI?
Citations allow staff, applicants, and the public to confirm answers directly in the adopted ordinance or plan, supporting defensibility and consistency.
Can generic AI replace planner judgment?
No. Planning-grade AI supports research and understanding while preserving staff authority and formal review processes.
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