discuss about Generative AI is now defined by its broad industry use and quick growth. With applications ranging from media production to healthcare, legal services, and finance, organizations are using large language models $($LLMs$)$ and associated technologies to increase productivity and creativity. With $$25\mathrm{.}2$ billion allocated to its development in $2023$nearly a $30-$fold increase since $2019$investment in generative AI has exploded. These days, technology is essential to many business operations, such as customer service, product development, and information technology. From general$-$purpose solutions to highly customized, domain$-$specific applications, generative AI technologies are becoming more and more specialized for particular industries. Notwithstanding its advantages, problems including inaccuracy, dangers to intellectual property, and the high computational expense of training sophisticated models continue to be significant obstacles. Businesses are implementing multi$-$model strategies and improving governance frameworks for responsible use in order to address these issues. Even though more people are aware of AI's revolutionary potential, worries about its ethical ramifications and employment effects still influence the conversation about its future.