Enhancing Decision-Making: From Raw Data to Strategic Insights for Business Growth

Organizations must make data-driven decisions to constantly adapt and alter their setting to remain viable. Artificial intelligence (AI) has become a phenomenon that has a significant impact on many business areas, especially when it comes to decision-making. AI has developed into an invasive tool that affects many business domains, such as crucial operations like decision-making. AI technological advances constant advancements have helped businesses optimize their operational and strategic planning. The prospective benefits of utilizing AI to propel ensemble machine learning (ML) for improving price strategies and optimizing revenues are examined in this study. The purpose of this research is to investigate how AI-powered ensemble ML may maximize price strategies by modeling business criterion prices to identify the best reduction techniques. To find patterns and linkages in the price statistics for strategic decision-making, three ensemble ML techniques are used as ML models on the database, which has 6562 possible tuples. The unique aspect of this study is how it illustrates how modeled statistics might improve company cost-cutting tactics. By highlighting the possibility of ML uses for company owners and employees engaged in manufacturing and advertising, this study adds to the body of research already available on AI and ML uses in business. The study's results have important ramifications for numerous sectors, such as sales, logistics, and transit.