Author
Listed:
- Grazyna Wiejak-Roy
- Ytzen van der Werf
- Zara Brewer
- Alex Kountourides
Abstract
Real estate businesses seek graduates not just with strong foundations so they can hit the ground running but increasingly more importantly with communication and reporting skills. Valuation, on top of technical skills, requires life skills such as attention to detail, proficiency in business writing and leveraging new technologies. This research provides a reflective account on a pedagogy experiment in which an AI-based valuation reporting tool was used in teaching and assessing postgraduate real estate students. While the AI-tool automates valuation report production (data gathering, mapping, report writing, templating, and audit trails) and avoids AI hallucinations by integrating information, it helps increase the accuracy of valuations. However, it does not generate advice-type outputs, which means that it does not replace valuers and still requires them to provide inputs based on their knowledge and professional judgment. The reflective account includes dilemmas around (1) the need to embed PropTech in teaching real estate valuation; (2) dealing with academic institutions’ reactive approaches to formally embracing technological innovations; (3) approaches to designing assessments embedding specific AI solutions; and (4) potential benefits of using AI-based PropTech in real estate education. Our observations suggest a great potential for AI-based PropTech in real estate education. However, this does not come without challenges that must be overcome by educators and their institutions.
Suggested Citation
Grazyna Wiejak-Roy & Ytzen van der Werf & Zara Brewer & Alex Kountourides, 2025.
"Teaching Real Estate Valuation – AI for report writing,"
ERES
eres2025_291, European Real Estate Society (ERES).
Handle:
RePEc:arz:wpaper:eres2025_291
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Keywords
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JEL classification:
- R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
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