Uppsats

Artificiell Intelligens vid Mergers & Acquisitions En kvalitativ studie om hur Artificiell Intelligens påverkar den kommersiella Due Diligence-processen vid Mergers & acquisitions.

Kandidat-uppsats

Göteborgs universitet/Företagsekonomiska institutionen

Publicerad: 2024-03-06

Språk: Svenska

Sammanfattning

This thesis explores the impact of Artificial Intelligence on the Due Diligence process in Mergers & Acquisitions. The study focuses on the integration of AI in streamlining and enhancing the efficiency of the DD process, traditionally known for being extensive and time-consuming. Through qualitative research, involving interviews with professionals from leading consulting firms, the study evaluates how AI technologies are currently being utilized, their potential for full integration into DD processes, and the associated challenges and benefits. Key findings indicate that while AI has not yet been fully integrated into DD processes, it is being used to support various tasks, such as data analysis and report generation. The potential of AI to process large amounts of data quickly suggests a future where it could significantly enhance the efficiency of information gathering and analysis phases in DD. However, challenges related to IT security, data confidentiality, and source verification limit the full adoption and trust in AI within these processes. The study also addresses concerns about the reliance on AI and the need for human oversight to ensure accurate and reliable results. Furthermore, the research discusses the implications of AI on the future of job roles and required competencies within M&A DD, highlighting the potential for junior employees to engage in more analytical work sooner. The thesis concludes that while AI has the potential to revolutionize DD in M&A, a balance between technological capabilities and human expertise is crucial for its successful integration. The future trajectory of AI in DD will likely involve it as a complement to human analysis rather than a complete substitute.

Information

Lärosäte / institution
Göteborgs universitet/Företagsekonomiska institutionen
Publiceringsdatum
2024-03-06
Uppsatstyp
Kandidat-uppsats
Språk
Svenska