Model management is a critical practice in the realm of data science and artificial intelligence. It involves the systematic organization, deployment, monitoring, and maintenance of machine learning and AI models throughout their lifecycle. Effective model management ensures that these models perform optimally, remain up-to-date, and align with evolving business needs. It encompasses various aspects, from version control and scalability to compliance and collaboration between data scientists and IT operations teams. Ultimately, model management is instrumental in harnessing the full potential of AI technologies to drive data-driven decision-making and innovation in organizations across diverse industries.