With advancing technology and digitalization, our capacity for data and information collection is exponentially increasing. Every day, terabytes of data are generated, and these data sets are becoming increasingly complex. AI technology is frequently used to analyze and evaluate these complex data sets. AI not only analyzes the data but also learns from it, understands it, and uses it to predict future trends. Therefore, the use of real-time data in AI models is extremely important.
Real-time data is high-volume data collected during or immediately after a specific event occurs. This data allows AI algorithms to achieve more accurate and effective results. Real-time data flow enables AI to understand, analyze, and make quick decisions on complex problems. This is particularly crucial for businesses and governments in making strategic decisions and creating emergency responses.
AI is used in many fields and plays a significant role in banking and finance, healthcare, e-commerce, transportation, and retail sectors. In banking, AI algorithms detect credit fraud and assist in risk management based on real-time data analysis. In the healthcare sector, real-time data is used to monitor patient conditions, perform health screenings, and determine treatment plans.
In e-commerce, AI uses real-time data collected from websites and applications to understand customers’ shopping preferences, behaviors, and habits. This information is used to create more accurate and personalized product recommendations, direct marketing strategies, and enhance customer satisfaction.
In the transportation sector, real-time data is used to optimize traffic flow and prevent accidents. AI analyzes incoming data to determine the most efficient routes, considering traffic density, weather conditions, and road conditions.
In the retail sector, AI uses real-time data collected through physical and online stores to manage inventory, predict sales, and optimize the customer experience.
AI PROVIDES A STRATEGIC ADVANTAGE! Thanks to real-time data, AI technology enhances instant decision-making capabilities and makes sensitive and accurate predictions. However, the correct use of real-time data in AI models requires substantial analytical capacity and robust infrastructure. Additionally, data security and privacy are important, as large amounts of personal or sensitive data may be collected. The combination of real-time data and AI allows us to quickly respond to unexpected events and make predictions. This provides us with a strategic advantage to make better decisions in personal, social, and business contexts.