The Role of Artificial Intelligence in Logistics Real Estate Investment Management for Sustainable Development and Strategic Decision-Making
Purpose: The purpose of this paper is to analyze how artificial intelligence (AI) supports investment management in the logistics real estate sector, emphasizing its impact on sustainable development and strategic decision-making. The study explores the ways in which AI technologies improve energy efficiency, optimize resource utilization, and enhance the resilience and profitability of logistics real estate investments. Design/Methodology/Approach: The research is based on a comprehensive analysis of secondary data, including academic literature, industry reports, and case studies of companies implementing AI in logistics property management. The study applies comparative and descriptive methods to evaluate the influence of AI on energy management, risk assessment, and sustainable investment strategies, with particular attention to the practices of JLL and Patrizia SE. Findings: The findings indicate that AI significantly improves decision-making processes in logistics real estate by enabling predictive analytics, market forecasting, and real-time energy optimization. AI applications contribute to reducing operational costs, mitigating investment risks, and achieving ESG (Environmental, Social, and Governance) objectives. However, the implementation of AI technologies also poses challenges, including high initial costs, system integration complexity, and the need for specialized expertise. Practical implications: The study demonstrates that AI-driven tools can support investors in aligning profitability goals with sustainable development strategies. The presented decision-support model for logistics real estate investment management provides a framework for integrating AI into portfolio optimization, risk management, and environmental performance monitoring. Originality/value: This paper contributes to the growing body of research on the intersection of artificial intelligence and sustainable investment management. It offers a structured approach to understanding how AI can transform logistics real estate into a more efficient, data-driven, and environmentally responsible investment sector.