As the global imperative for sustainable development intensifies, the real estate industry stands at the intersection of environmental responsibility and economic viability. This paper presents a comprehensive exploration of the significance of sustainable solutions within the real estate sector, employing advanced artificial intelligence (AI) algorithms to assess their impact. This study focuses on the integration of AI-powered tools in a decision-making process analysis. The research methodology involves the development and implementation of AI algorithms capable of analyzing vast datasets related to real estate attributes. By leveraging machine learning techniques, the algorithm assesses the significance of energy efficiency solutions along with other intrinsic and extrinsic attributes. This paper examines the effectiveness of these solutions in relation to the influence on property prices with a framework based on an AI-driven algorithm. The findings aim to inform real estate professionals and investors about the tangible advantages of integrating AI technologies into sustainable solutions, promoting a more informed and responsible approach to industry practices. This research contributes to the growing interest in the connection of the real estate sector, sustainability, and AI, offering insights that can guide strategic decision making. By implementing the random forest method in the real estate feature significance assessment original methodology, it has been shown that AI-powered algorithms can be a useful tool from the perspective of real estate price prediction. The methodology’s ability to handle non-linear relationships and provide insights into feature importance proved advantageous in comparison to the multiple regression analysis.

Real estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very important fact that should be underlined is that properties are strongly related to geolocation (space) and strongly determine it. Authors proposed in the paper solutions that highlight implementation of geoscience and “geo-approach” combined with fuzzy logic methods that allow to decrease subjectivity in property analyses and diminish uncertainty in decision making process. The proposed methodology involves three main problematic components of decision support system in property investment analyses development with the use of geo-technologies such as: determination of the database model; elaboration geo-property-zones with geoprocessing activities; identification of homogeneous group of properties transactions. The influence of spatial decision factor determined in the study lead to objective and precise calculation of value differentiation from 22 to 43% depending on the property’s remoteness to the sea.

Research undertaken by the World Bank in Europe and the Central Asia Region indicates that there are four principal preconditions for introducing value-based recurrent property tax reforms: comprehensive property registration, a reliable source of data about the prices achieved in transactions, a valuation infrastructure that complies with internationally-recognized standards, and an efficient tax collection system. In spite of the arguments in favor of value-based recurrent property taxes, many countries raise revenue from recurrent property taxes using an area basis, and most countries raise relatively little revenue from recurrent property taxes. The paper has been written according to both the dogmatic-legal method and comparative method. It presents current solutions adopted in post-Soviet European countries in order to draw out recommendations and suggestions for Poland. The original reasoning for the paper is that, amongst many scientific papers concerning thorough debate of property tax systems, few have focused on post-Soviet countries and the issues that arise in transition countries. Most concern Western European or North American countries with different economies, politics, institutions, and histories to the Eastern ones. Authors of the paper believe that the article can fill the gap in discussions on the shape of the property tax system reform in Poland and the reforms carried out in Eastern Europe countries.