Leveraging Artificial Intelligence for Target Screening: A Targeted Research Paper Aiming to Highlighting the Potential of LLM's Within the M&A Industry

Abstract

The rapid advancement of Artificial intelligence is a significant driver for economic and strategic transformation. The technology is set to boost the global GDP by $15.7 trillion before 2030. Despite its increasing prevalence, the adoption of AI in businesses remains uneven, with 25% of global companies currently integrating AI into their operations the mergers & acquisitions industry remains relatively slow at embracing AI, with only 16% of transactional advisory firms utilizing AI. Based on an identified lack of research within the implementation of AI solutions in M&A processes, a further investigation of the area was conducted through interviews with professionals in the industry. The interviews supported the reported low rate of adoption found in reports, and further highlighted the screening process to be the most time consuming. From this identified gap the thesis aims to 1) analyze the potential of integrating AI withing this process, and 2) provide potential reasons to why this gap in literature and adaptation exists. By employing a qualitative research design, the study incorporates a systematic literature review, interviews with M&A professionals, and practical applications of a prompt framework using ChatGPT to demonstrate AI's value in the screening process. The findings indicate that M&A firms can sustainable competitive advantages by integrating AI in the screening process. But substantiates the importance developing internal capabilities that support the integration of AI technology. Further, the findings suggest that the gap of implementation is a result of the combination between, A) a lack of AI supporting capabilities inherent to the M&A industry and B) that AI is not yet mature enough to handle the complex and nuanced landscape of M&A analysis.