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Advisor(s)
Abstract(s)
Esta dissertação tem como objetivo avaliar o estado atual da adoção de tecnologias de Inteligência Artificial (IA) no setor imobiliário português, bem como identificar os principais benefícios e barreiras associados à sua implementação e os principais impactos observáveis. A investigação baseia-se num estudo quantitativo, utilizando um questionário respondido por 228 profissionais do setor imobiliário. Os resultados indicam que, embora a adoção de IA esteja em crescimento, ainda é um fenómeno relativamente recente. As principais vantagens percecionadas incluem o aumento da eficiência operacional e a melhoria na tomada de decisões, enquanto a complexidade tecnológica e a falta de compatibilidade com sistemas existentes são apontadas como as maiores barreiras. A análise revela que áreas como a avaliação de imóveis e a recomendação personalizada de propriedades são as mais influenciadas pela IA, com impacto positivo significativo. Por outro lado, áreas como a previsão de preços e o atendimento ao cliente apresentam uma adoção mais lenta. Este estudo oferece insights valiosos sobre o potencial e os desafios da adoção de Inteligência Artificial (IA) no setor imobiliário português, focando-se na área da mediação imobiliária.
This dissertation aims to assess the current state of adoption of Artificial Intelligence (AI) technologies in the Portuguese real estate market, as well as to identify the main benefits and barriers associated with its implementation, and the most observable impacts. The research is based on a quantitative study, using a survey answered by 228 professionals in the real estate market. The results indicate that although AI adoption is growing, it is still a relatively recent phenomenon. The main perceived advantages include increased operational efficiency and improved decision-making, while technological complexity and lack of compatibility with existing systems are identified as the biggest barriers. The analysis reveals that areas such as property valuation and personalized property recommendations are the most impacted by AI, with significant positive effects. On the other hand, areas such as price forecasting and customer service show slower adoption. This study provides valuable insights into the potential and challenges of Artificial Intelligence (AI) adoption in the Portuguese real estate sector, with a particular focus on real estate brokerage.
This dissertation aims to assess the current state of adoption of Artificial Intelligence (AI) technologies in the Portuguese real estate market, as well as to identify the main benefits and barriers associated with its implementation, and the most observable impacts. The research is based on a quantitative study, using a survey answered by 228 professionals in the real estate market. The results indicate that although AI adoption is growing, it is still a relatively recent phenomenon. The main perceived advantages include increased operational efficiency and improved decision-making, while technological complexity and lack of compatibility with existing systems are identified as the biggest barriers. The analysis reveals that areas such as property valuation and personalized property recommendations are the most impacted by AI, with significant positive effects. On the other hand, areas such as price forecasting and customer service show slower adoption. This study provides valuable insights into the potential and challenges of Artificial Intelligence (AI) adoption in the Portuguese real estate sector, with a particular focus on real estate brokerage.
Description
Keywords
Inteligência Artificial Setor Imobiliário Adoção de Tecnologia Difusão da Inovação Benefícios Barreiras Artificial Intelligence Real Estate Technology Adoption Innovation Diffusion Benefits Barriers
Pedagogical Context
Citation
Fonseca, Patrícia Alexandra de Jesus .(2024). “A adoção de tecnologias de inteligência artificial no setor imobiliário português”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão
Publisher
Instituto Superior de Economia e Gestão