Fast is how Gen AI has shaped industries digitally: it has changed the way we really live and work now in this transforming world and impacts the potential to embrace $15.7 trillion to the economy by 2030. Against this background, the currently proposed research would focus on tapping the powers of Gen AI to make narrative summarization, which is an important task within natural language processing, interactive, by designing and evaluating novel hybrid Gen AI models for summarizing long, comprehensive financial reports in overviews that key stakeholders would find easy to appreciate in terms of the main tenets of financial narratives. It will be achieved through the combination of today’s and new-cutting technologies and methodologies, such as large language models, transformer-based architectures, and reinforcement learning algorithms that result in a summarization of relevancy and preciseness. The test will be put into force on an extensive data set of financial reports involving a suite of evaluation metrics covering ROUGE scores, human evaluation metrics, financial metrics like return on investments, earnings per share, among others. In-depth analysis of the results will be done, comparing strengths and weaknesses of the methods chosen. These have broader implications for the development of better summarization systems of the financial narratives which can be useful for stakeholders to decide on informed decisions driving the growth in business.