Georgia County Transforms Residential Property Appraisal with AI-Driven Workflows

Overview

The Georgia County Tax Assessor is responsible for assessing property values in a populous Georgia County. Home to over 760,000 residents and 255,000 single-family homes, townhomes, and condominiums, the Georgia County encompasses a rapidly growing residential landscape. To support this growth, the Georgia County officials needed a scalable solution to deliver fair, timely, and transparent assessments, ultimately reinforcing public confidence in the appraisal process.

Business Need

The Georgia County Tax Assessor faced significant challenges in scaling its property appraisal process. Despite having strong in-house expertise, the team often lacked the time and resources to develop models at scale. As a result, they relied on third-party services to support property modeling, review, and appraisal — a process that often took months and created bottlenecks in assessments.

Additionally, much of the appraisal team’s time was spent manually reconciling data across different systems — reviewing property records, identifying discrepancies, and cleaning inconsistent data to ensure accurate valuations. These laborious processes strained capacity and made it difficult to maintain consistency and efficiency at scale. To address these challenges, the Georgia County Tax Assessor needed a solution that could streamline data workflows, accelerate model development, and deliver fast, defensible valuations without compromising accuracy.

The Solution

The Georgia County Tax Assessor partnered with C3 AI to deploy C3 AI Property Appraisal for all 255,000 single-family homes, townhomes, and condominiums in the County. Together, the joint team integrated data from the Computer-Assisted Mass Appraisal (CAMA) system, the Geographic Information System (GIS), and property listings in the county — automatically cleaning, validating, and unifying the data into a centralized data foundation. Building on this, the team developed AI-based Automated Valuation Models (AVMs) and other machine learning models to support mass appraisal, generating AI-driven condition scores, identifying relevant sales comparables, and delivering faster, more consistent valuations.

Results

C3 AI Property Appraisal improved property valuation accuracy by 27% — measured by the percentage of valuations within 15% of sale price — compared to the county’s baseline derived from historical CAMA appraisal values. The solution significantly improved operational efficiency for the Georgia County Tax Assessor’s Office. Model development and deployment timelines were reduced from several months to under two weeks, and data cleaning — previously a multi-year, manual effort — was completed in hours through automated processing. These time savings not only improved appraiser speed and accuracy, but also allowed staff to focus on strategic, high-priority initiatives that had previously been delayed due to resource constraints.

About the Georgia County

• $50+ billion in total assessed property value
• 760,000+ residents — one of the most populous counties in Georgia
• 6 municipalities
• Top 100 U.S. counties by median household income

Project Highlights

• 255,000+ residential properties (single-family homes, townhomes, and condominiums) in-scope
• 4 years of historical data integrated from 3 data sources (CAMA, listing data, and GIS)
• 2 ML models configured to generate fair market values for in-scope properties
• 1 large language model (LLM) configured to generate AI-based condition ratings based on MLS imagery
• +27% increase in valuation accuracy, improving compliance with International Association of Assessing Officers (IAAO) benchmarks

“What used to take us six weeks is now going to take us one day. C3 AI is helping us save a considerable amount of time.”  

— Chief Appraiser