## 5 Conclusions  
This paper introduces the concept of the decision-making system in homogeneous property market analyses, named HELIOS. The system responds to the increasing demand for solutions that facilitate successful collaboration between humans and machines in a user-friendly manner. HELIOS pioneers a novel concept grounded in linguistic intelligence and machine learning to reshape how real estate data is perceived and analyzed in a world increasingly focused on AI. By exploring synergies between human expertise and technological capabilities, HELIOS aims not only to enhance real estate analyses' efficiency but also to contribute to sustainable and responsible data practices in dynamic property markets. The intricate nature of the property market poses a challenge, especially in mass appraisals associated with taxes, which are sensitive and collectively vital aspects. Despite this complexity, we often rely on straightforward analytical tools and models, presenting a paradox. This complexity is particularly pronounced in mass appraisals, emphasizing the need for sophisticated solutions.  
The suggested method is crucial for linking AI-based data processing with human expertise. It guarantees that the HELIOS system stays precise, dependable, and useful in the ever-changing and intricate real estate market. The proposed HELIOS system offers a practical application as an alternative solution that can be utilized in several critical stages of property valuation within systems such as automated valuation models (AVMs):  
1. Homogeneous Market Definition: HELIOS leverages advanced machine learning and linguistic intelligence to define homogeneous market areas, ensuring accurate mass appraisals.
2. Comparable Properties Set Definition: HELIOS accurately selects comparable properties by analysing their characteristics comprehensively. In CAMA systems, HELIOS can further enhance:  
1. Data Review and Validation: HELIOS reviews and validates data, identifying inconsistencies to ensure accuracy.
2. Exploratory Data Analysis: HELIOS uncovers patterns and trends, providing insights that improve the mass appraisal process.  
The paper acknowledges social threats associated with AI applications, including job displacement, wealth inequality, academic dishonesty, biases, prejudices, hallucinations, and the challenge of dismantling AI's \"black box\" nature. However, human nature's resilience and understanding of AI's potential for positive impact encourage real estate analysts to leverage this technology.  
Fortunately, human nature has embraced the brighter side of things. Instead of fearing and avoiding the topic, it has chosen to understand better, familiarize, and develop the subject. This approach allows for the control of this phenomenon. Consequently, real estate analysts have little choice but to maximize the utilization of this technology, aiming to amplify its benefits over its drawbacks.  
Future research will focus on developing solutions for the problems mentioned in homogeneous market analyses, with results verifying HELIOS's efficiency and adequacy of the decision-making system.  
All authors declare equal participation in every activity related to the creation of the article. All authors have read and agreed to the published version of the manuscript.  
This research was partially funded by the National Science Center [Grant number 2023/49/B/HS4/00701].  
Data Availability Statement: Data sharing is not applicable to this article, due to source data was provided to the authors solely for closed scientific research.  
The authors declare no conflicts of interest.