The field of artificial intelligence is rapidly advancing, with generative AI (GenAI) gaining significant public attention. Traditional AI has long supported enterprise operations, but GenAI introduces new capabilities and perceptions. Understanding the distinctions between these AI types is crucial for strategic IT decisions. This discussion will outline the core differences, applications, and implementation needs of traditional and generative AI. The choice between them hinges on understanding your business use case, infrastructure, and IT processes. Complex, structured analysis favors traditional AI, while adaptive applications benefit from GenAI. For creative tasks requiring original content, GenAI is superior to traditional AI's rule-based approach. Generative AI demands extensive datasets and computing power, unlike traditional AI, which can operate with smaller structured data. Organizations must carefully consider these factors when selecting the appropriate AI. Caution is advised when using third-party GenAI tools with sensitive information due to potential data usage for training.