The tourism sector, traditionally known for its conventional structure, is evolving into a system based on artificial intelligence and data analytics with digital transformation. The domestic software Elektraweb, used in more than 4,000 hotels in Turkey, stands at the center of this change. Teoman İbili, Chairman of Elektraweb Software Group, emphasized that “It is no longer just about selling rooms; effective use of data and developing strategies based on it is crucial,” highlighting that the new era in tourism is a data-driven management model.
Management Through Data Processing
From guest movements in hotels to energy consumption, purchasing, and waste management, every area is now controlled by data-driven systems. Thanks to these systems, hotels gain advantages in many areas such as sustainability, cost reduction, and service quality improvement. AI-supported systems extract meaningful insights from data, enabling businesses to make strategic decisions. İbili stated, “Hotels can now collect guest data from different countries, purchasing habits, and consumption details into shared systems and perform integrated analyses. This is revolutionary for both environmental sustainability and operational profitability.”
Especially in Europe and North America, many hotel chains invest in AI-supported energy and waste management systems to reduce their carbon footprint. “Smart Guest Room” systems automatically prepare the room based on guests’ previous stays. The tourism sector now offers an experience shaped not only by physical service but also by data, technology, and human interaction.
Businesses adopting AI-supported systems gain advantages in many areas, from sustainability to customer satisfaction, while hotels unable to read and use data face inevitable exclusion from competition. Thanks to projects conducted with Turkey’s Ministry of Culture and Tourism, anonymized data collected from hotels are used as reference data in shaping tourism policies. As a result, regional investments, seasonal pricing, and tourist profile analyses are becoming more data-driven.
