Modeling Pricing Strategies Using Artificial Intelligence Algorithms

In the context of digital economic transformation and heightened market uncertainty, traditional pricing methods are increasingly losing their effectiveness. This article explores the application of artificial intelligence algorithms for developing adaptive and resilient pricing strategies. Particular attention is devoted to forecasting consumer behavior, modeling competitive dynamics, and multi-objective profit optimization that accounts for risk and external factors. Empirical examples from various industries are presented to demonstrate improvements in margin performance and business resilience achieved through the integration of artificial intelligence into pricing processes. The study substantiates the necessity of transitioning from static pricing models to intelligent systems capable of real-time learning and adaptation.