The Role of Artificial Intelligence in Enhancing Decision-making and Efficiency in Mergers and Acquisitions: A Case Study Approach within the U.S. Capital Market.

This study explores the role of artificial intelligence (AI) in enhancing decision-making and operational efficiency in mergers and acquisitions (M&A) within the U.S. capital market. In recent years, AI technologies have been increasingly adopted to support various stages of the M&A process, including target identification, due diligence, valuation, and integration. The primary aim of this research is to examine how AI contributes to improved outcomes in M&A transactions and to assess the associated risks and limitations. The study employs a case study methodology, analyzing selected M&A transactions where AI tools were integrated into strategic and operational decision-making. The findings indicate that AI significantly reduces the time and cost associated with due diligence, enhances data accuracy, and supports better forecasting and scenario analysis. Furthermore, the study revealed that AI enables more objective decision-making by minimizing cognitive bias and processing large volumes of structured and unstructured data. The study also identifies several challenges. These include concerns about data privacy, cybersecurity risks, the transparency of AI algorithms, and the potential legal implications of relying on automated systems. The research highlights the need for comprehensive legal frameworks and ethical guidelines to govern the use of AI in M&A. In conclusion, AI has the potential to transform the M&A landscape in the U.S. capital market by improving efficiency, accuracy, and strategic clarity. Nevertheless, its successful integration requires careful attention to legal, ethical, and regulatory considerations.