M. Sc. Danielle Warstat

Acceptance of Artificial Intelligence in Real Estate Valuation

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Motivation

The use of artificial intelligence (AI) has grown steadily in recent years. The potential applications are diverse, such as large language models or neural networks. Today these are primarily used for support functions, such as text generation or the automatic extraction of information from documents. The use of AI methods for actual calculations is limited by appraisers and valuation experts. In contrast to parametric methods, the challenge is the ‘black-box’ nature of the most models. Another challenge is the legal framework. These uncertainties have a significant impact on the acceptance of these methods. However, such acceptance is necessary in order to integrate the potential of AI profitably into the working environment. This can lead to efficiency gains that help counteract the effects of the shortage of skilled workers.

The opportunities and challenges of AI have already been examined in various publications. To date, little research has conducted into the acceptance of AI methods in the practice of real estate valuation. In other specialist fields, various factors influencing the acceptance of AI have been identified. Furthermore, there is a lack of analyses on how the acceptance and the use of these methods in the field of real estate valuation can be increased.

Main Goal

This thesis aims to examine in detail the acceptance of AI methods by appraisers and valuation experts, in order to make the best possible use of the technology’s advantages. To this end, the level of acceptance will be assessed to identify specific influencing factors. These will be considered in relation to the organisational and legal frameworks in Germany and Austria. The aim is to identify positive influences and translate these into concrete recommendations for action.

On this basis, the following research questions will be addressed in the dissertation:

To what extent can Germany and Austria learn from one another with regard to the use of artificial intelligence in real estate valuations?

• How high is the level of acceptance of artificial intelligence in the context of real estate valuation in Germany and Austria?
• What positive and negative factors influence the acceptance of artificial intelligence in Germany and Austria respectively?
• How can acceptance be increased?

Methodology

A mixed-methods approach is adopted to answer the research questions.

Firstly, the underlying concepts will be analysed as part of a literature review. This will identify the individual factors influencing acceptance for the quantitative survey. The target group for the survey consists of individuals who carry out real estate valuations. In addition to the relevance of these influencing factors, the impact of the organisational and legal frameworks in Austria and Germany will also be analysed on the basis of interviews and literature reviews. The results of the quantitative survey will be discussed in relation to the similarities and differences between Germany and Austria in workshops with experts. The goal is deriving recommendations for action. These will then be validated through qualitative interviews.

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