Overview

Original Research

ARE AVMs THE SAME AS AI METHODS? A LITERATURE REVIEW

C. TULIKUNO*, S.H.P. CHIKAFALIMANI, M.S RAMABODU and N. KIBWAMI

Vol 20, No 11 ( 2025 )   |  DOI: 10.5281/zenodo.17617049   |   Author Affiliation: Department of Construction Management & Quantity Surveying, Faculty of Engineering and The Built Environment, Durban University of Technology, Durban, South Africa 1, Department of Construction Management & Quantity Surveying, Faculty of Engineering and The Built Environment, Durban University of Technology, Durban, South Africa 2, Department of Construction Management & Quantity Surveying, Faculty of Engineering and The Built Environment, Durban University of Technology, Durban, South Africa 3, Department of Construction Economics and Management, School of the Built Environment, College of Engineering, Design, Art and Technology, Makerere University, Kampala, Uganda 4   |   Licensing: CC 4.0   |   Pg no: 68-77   |   Published on: 15-11-2025

Abstract

This review examines whether Automated Valuation Models (AVMs) and Artificial Intelligence (AI) are synonymous within real-estate valuation. Drawing on 37 academic and grey-literature sources (including IVS, RICS, IAAO, and recent empirical studies), the paper clarifies the conceptual and operational relationships between AVMs, CAMAs, and AI/ML methods. The results indicate that AVM is a domain-level framework for automated property valuation that has historically used statistical or rule-based methods (like hedonic regression). On the other hand, AVMs can utilise AI, a group of adaptive algorithms: Neural networks, tree ensembles, SVMs, and computer vision. Modern AVMs form a spectrum—from purely statistical to fully AI-driven systems—and AI generally improves predictive accuracy and enables use of novel, unstructured data (images, text, geospatial metrics). However, AI-enhanced AVMs raise challenges in terms of interpretability, data quality and privacy, regulatory acceptability, and professional oversight. The review concludes that AVM ≠ AI, but AI is increasingly integral to state-of-the-art AVMs; it recommends standardised terminology, comparative evaluations across market types, explainable and auditable AI methods, and hybrid human–AI workflows to balance predictive gains with transparency and accountability.

Keywords

Automated Valuation Models (AVMs); Artificial Intelligence (AI); Machine Learning (ML); Real Estate Valuation; Computer-Assisted Mass Appraisal (CAMA)