Modern Technology Adoption in Property Valuation: Perceptions in South Africa

Abstract: Emerging technologies such as artificial intelligence (AI), automated valuation models (AVMs), geographical information systems (GIS) and other related technologies are reshaping the global property valuation industry. Debates on readiness for the adoption of digital technologies are at the forefront particularly in municipal valuations, where concerns of valuation accuracy are prevalent. This study investigates how property valuers perceive and adopt AI and other technologies in South Africa. The study employed a quantitative research design using an online national questionnaire survey distributed to capture the opinions of property valuers. A total of 340 valid responses were received and analysed using Statistical Package for Social Sciences (SPSS) version 30. Descriptive statistics, Spearman’s rank-order correlation, Kruskal–Wallis H tests, and Pairwise Mann–Whitney U tests were applied to determine relationships and group differences. Findings indicate that AI adoption is minimal, with nearly half of property valuers reporting “never” using AI tools such as “ChatGPT” and only 1.8% reporting regular use. Statistically significant differences in adoption were observed across specialisation and registration class, with commercial and candidate valuers demonstrating higher adoption rates. Conversely, municipal and senior valuers displayed more conservative digital engagement patterns. Candidate valuers and valuers with less experience were more likely to experiment with AI tools, while property valuers specialising in municipal valuers were reported to be the most resistant to the use of AI and related emerging technologies. Confidence in GIS tools showed a high adoption rate with most respondents reporting consistent use. The findings indicate that South African property valuers are concomitantly progressive and conservative, with the use of GIS tools fully integrated in practice while AI and AVMs are yet to be adopted.

Keywords: Artificial Intelligence (AI), Geographical Information Systems (GIS), Automated Valuation Models (AVMs), Technology adoption, South Africa

DOI: 10.54941/ahfe1007151

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