M. Sc. Danielle Warstat

Acceptance of Artificial Intelligence in Real Estate Valuation

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Motivation

The use of artificial intelligence (AI) has steadily increased in recent years. Its potential applications are diverse, including large language models, neural networks, and automatic image recognition. Currently, these are primarily used for support services, such as text generation or automatic document extraction. The use of AI methods for actual calculations is limited in practice. In contrast to parametric methods, the challenge is the ‘black-box’ nature of the most models. Another challenge is the legal framework. These uncertainties significantly influence the acceptance of these methods. However, such acceptance is necessary to profitably make the most of the potential and integrate them into the work environment. This can lead to efficiency gains that help counteract the effects of the skilled labor shortage.

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

Main Goal 

This thesis aims to examine the acceptance of AI methods in practice in greater detail in order to make the best possible use of the technology’s advantages. To this end, the level of acceptance will be determined to identify specific influencing factors. These will be contextualized within the organizational and legal framework conditions of Germany and Austria. The goal is to identify positive influences and translate them into concrete recommendations for action.

Based on this, the dissertation aims to answer the following overarching research question:

To what extent can Germany and Austria learn from each other regarding the use of artificial intelligence in real estate appraisals?

This is further specified by the following questions:

• How high is the 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 used to answer the research questions (Fig. 1).

First, the substantive foundations will be evaluated through a literature review. This review will identify the individual factors influencing acceptance for the quantitative survey. The survey’s target group consists of individuals who conduct real estate appraisals. In addition to the relevance of these influencing factors, the impact of organizational and legal framework conditions in Austria and Germany will be analyzed through interviews and literature reviews. The results of the quantitative survey will be discussed in workshops with experts, taking into account the differences and similarities between Germany and Austria. Recommendations for action will then be derived from these discussions.

© Warstat