In today's AI landscape, traditional machine learning (ML) and generative AI (GenAI) represent two distinct approaches to problem-solving. Traditional ML is data-driven and precise, excelling in areas like fraud detection and time-series forecasting where data is well-understood and problems are well-defined. GenAI, on the other hand, is broad, flexible, and capable of reasoning across various domains without strict rules, forming the basis of large language models and intel