In today's highly competitive and data- driven marketplace, pricing strategy has become a decisive factor in determining a company's profitability, customer satisfaction, and long-term sustainability. Traditional static pricing models, which rely on fixed markups or manually updated price lists, are often inadequate in responding to the dynamic nature of modern markets. These methods struggle to adapt to frequent fluctuations in consumer demand, competitor actions, supply chain disruptions, and seasonal influences. This research presents the design and development of an Artificial Intelligence (AI)-based Dynamic Pricing Engine that autonomously predicts and optimizes product prices in real time. The proposed framework integrates a variety of heterogeneous data sources — including historical sales transactions, customer purchasing behavior, inventory levels, market demand elasticity, and competitor pricing trends — to generate context-aware pricing recommendations. The system employs a hybrid machine learning approach: regression-based models are used for short- term price prediction, while reinforcement learning techniques enable continuous self-improvement through feedback-driven optimization. A prototype implementation was tested using real-world re- tail and e-commerce datasets to evaluate its effectiveness. The experimental results demonstrate that the AI-driven dynamic pricing model significantly enhances revenue optimization, profit margins, and inventory turnover compared to traditional rule- based or static pricing systems. Moreover, the model exhibits rapid adaptability to demand shifts and improved decision- making accuracy under volatile market conditions. The findings highlight the transformative potential of AI in automating strategic business decisions and emphasize the scalability and robustness of intelligent pricing systems. This study contributes to the broader field of intelligent commerce by providing a data-centric, adaptive, and scalable solution for modern enterprises seeking to maintain competitiveness in the evolving digital economy.