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AI exposure report

Will AI replace Urban and Regional Planners?

Some of your tasks will be automated. People who use AI will have the edge.

Task exposure to today's AI

48/100

Moderate exposure

This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.

Get your personal score

Will AI replace Urban and Regional Planners?

Not entirely. Today's AI tools can take on about 48% of the typical work in this occupation, mostly: create, prepare, or requisition graphic or narrative reports on land use data, including land area maps overlaid with geographic variables, such as population density. The parts that stay human include: Hold public meetings with government officials, social scientists, lawyers, developers, the public, or special interest groups to formulate, develop, or address issues regarding land use or community plans.; Design, promote, or administer government plans or policies affecting land use, zoning, public utilities, community facilities, housing, or transportation.; Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives..

People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.

Which tasks AI can take on

The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.

TaskAutomatable
Create, prepare, or requisition graphic or narrative reports on land use data, including land area maps overlaid with geographic variables, such as population density. 70%
Assess the feasibility of land use proposals and identify necessary changes. 60%
Respond to public inquiries and complaints. 57%
Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives. 47%
Design, promote, or administer government plans or policies affecting land use, zoning, public utilities, community facilities, housing, or transportation. 45%
Hold public meetings with government officials, social scientists, lawyers, developers, the public, or special interest groups to formulate, develop, or address issues regarding land use or community plans. 15%

+ 19 more tasks (59% of the week) in the full test.

Your human edge

  • Hold public meetings with government officials, social scientists, lawyers, developers, the public, or special interest groups to formulate, develop, or address issues regarding land use or community plans.
  • Design, promote, or administer government plans or policies affecting land use, zoning, public utilities, community facilities, housing, or transportation.
  • Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives.

AI tools to try

ChatGPT / Claude for literature and writingAI research tools (e.g. Elicit, Consensus, Semantic Scholar)Copilot for data analysis code (Python, R)

Related roles

A 3-phase AI learning plan

Phase 1

Faster literature and writing

  • Literature search and summaries with AI, always checked against the papers.
  • Drafts of methods, reports and grant text.
  • Reference management and formatting.

Project

Use AI to summarise 20 comparable zoning ordinances and draft a 10-page staff report on a rezoning proposal, verifying every citation and halving your usual drafting time.

Phase 2

AI for data analysis

  • Analysis code in Python or R written with AI help.
  • Visualisation and statistics explained step by step.
  • Reproducibility: version code and prompts.

Project

Write AI-assisted Python or R code to map and chart five years of permit and census data for one district, producing three reproducible visuals with versioned code and prompts.

Phase 3

AI as a research method

  • Classification, extraction or modelling with AI on your data.
  • Validate against human labels or ground truth.
  • Ethics, data protection and disclosure of AI use.

Project

Use AI to classify 300 public hearing comments by theme and sentiment, validate against 50 hand-coded comments, and report accuracy plus an AI-use disclosure note.
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