Author
Listed:
- Mabel Weber
- Daniel Piazolo
Abstract
The integration of artificial intelligence (AI) in real estate companies has become a focal point for enhancing operational efficiency and gaining competitive advantages. This study examines the potentials and challenges associated with the adoption of AI within the real estate sector. There is a wide range of the preparedness of the companies, some firms have embraced mature AI strategies whereas some enterprises are still in the initial phases of this transformative process. Qualitative interviews with industry experts serve as the foundation of this study, offering insights into the experiences, hurdles, and prospects within the industry. A qualitative content analysis of these interviews illuminates the diverse perspectives on the application, challenges, and impacts of AI in real estate. The analysis reveals a spectrum of AI implementation across companies, with some leveraging advanced applications like data-driven decision-making and smart building technologies, while others focus on streamlining foundational processes. Key challenges in AI implementation within the real estate domain include data availability, technological integration, workforce acceptance, and training. Furthermore, the findings underscore that successful AI integration hinges not solely on technological advancements but also on organizational readiness and human factors. Factors such as openness to change, investment in training initiatives, and strategic collaborations with external partners emerge as critical determinants of success. In conclusion, this study underscores the substantial potential of AI adoption in augmenting operational efficiency and fostering competitiveness within the real estate industry. However, the journey towards successful AI integration necessitates a holistic approach that considers technological, legal, and social dimensions. This research contributes insights for real estate companies looking to navigate the evolving landscape of AI implementation, offering guidance on mitigating challenges and harnessing the transformative power of artificial intelligence.
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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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