Municipal AI Transition Checklist

3.70

Derivation Chain

Step 1 Municipal AI administrative transformation

→

Step 2 AI adoption consulting/assessment

→

Step 3 AI transition progress self-assessment and benchmarking tool

Problem

All 226 basic municipal governments across Korea (e.g., Hoengseong County) are pursuing AI-driven administrative transformation, but lack standardized tools to systematically track AI adoption status across departments, forcing officials to manage everything manually in spreadsheets. Duplicate deployments across departments and inability to track progress waste hundreds of administrative hours annually, and compiling data for Ministry of the Interior and Safety (MOIS) evaluations alone takes 2–3 weeks.

Solution

A self-assessment checklist SaaS based on the MOIS AI administrative transformation evaluation framework. (1) Department-level AI adoption status dashboard, (2) auto-generated benchmarking Reports against similarly-sized municipalities, (3) one-click export of MOIS submission reports. Unlike generic AI adoption self-assessment kits, this focuses specifically on municipal administration with department-level tracking and benchmarking.

Target: Chief Information Officers / AI Transition Task Force leads at basic municipal governments (226 cities/counties/districts, Grade 6–7 officials)

Revenue Model: SaaS flat rate at $217/month per municipal account, 20% discount for annual contracts. Target ARR of $105,000 at 50 municipalities.

Ecosystem Role: Infrastructure

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

4.0/5

M Market

3.0/5

R Realizability

4.0/5

V Validation

4.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (70%)

Tech Complexity

29.3/40

Data Availability

20.6/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (57/100)

Competition

8.0/20

Market Demand

9.4/20

Timing

16.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

9.0/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Frontend [medium] Backend [medium] Data Pipeline [low]

Dashboard