Increasing Management Efficiency and Financial Results in Short-term Rental Using AI: The Case of Solarento and a Comparison of Competitor Models in Poland

Abstract:

The dynamic development of the short-term rental market in Europe, including Poland, has increased competition among apartment operators and raised property owners’ expectations regarding transparency, profitability, and quality of cooperation. This article presents a case study of Solarento, a new operator in the Polish market, which implemented advanced artificial intelligence (AI) tools within the first months of operation to increase apartment management efficiency and improve financial results for property owners.

The study is based on an analysis of AI deployments in areas such as dynamic pricing, demand forecasting, occupancy optimization, operations automation, and profitability analysis. Empirical data from the Polish market are benchmarked against competing companies—Sun & Snow and Downtown Apartments—showing how Solarento’s model differs in technology, transparency, and cooperation flexibility.

The results indicate that well-implemented AI can increase revenue predictability, reduce vacancies, enhance guest experience, and enable property owners to achieve higher net profits—even off-season. The article contributes to the discussion on digital transformation in the hospitality industry and emphasizes the importance of partnership and automation as sources of competitive advantage amid economic uncertainty and rising operational costs.