Generative Artificial Intelligence (AI) is a subset of deep learning where multi-layer neural network models generate new content such as text, images, audio, video, code, and synthetic data in response to natural language prompts based on what the models have learned from patterns in the content they were trained on. This technology is transforming business by assisting people, improving productivity, and automating tasks. Its benefits include improved productivity, real-time search, text generation, code generation, assisted metadata curation, and AI-automated actions. Generative AI is also emerging in almost every area of data management, including data engineering, data virtualization, data catalogs, business glossaries, data marketplaces, data governance, and more. It can help bridge the skills gap by enabling citizen data engineers to fill an increasing demand for data integration skills. Additionally, generative AI can assist non-technical users in finding data, generating code, explaining data pipelines, debugging, and optimizing code. Its applications extend beyond data creation to data consumption, where it provides natural language explanations of data products and queries, improving the efficiency of non-technical users. As this technology continues to evolve, tool vendors will likely implement reinforcement learning to create self-learning AI assistants, further democratizing and accelerating data management tasks.