The Italian energy sector is characterized by high price volatility (IPEX), increasing complexity in determining the Single National Price (PUN), and the need for highly agile, data-driven decision-making processes. In this context, traditional Decision Support Systems (DSS), primarily based on Business Intelligence (BI) tools and manual data aggregation, exhibit structural limitations regarding timeliness, integration of information sources, and the ability to support strategic decisions in highly uncertain environments. This thesis, developed within the framework of an industrial collaboration between Accenture and a major Italian energy player, proposes the strategic transition from traditional Business Intelligence systems toward the adoption of agentic systems based on Generative Artificial Intelligence, with the objective of evaluating their impact on operational efficiency and strategic value creation in an enterprise setting.