In this two-part article, the author explores the impact of artificial intelligence (AI) on the mergers and acquisitions (M&A) deal value chain. In this first part, the author provides a high-level overview of generative AI, discussing recent advancements and applications across various industries. He then delves into how AI is used at different stages of the M&A deal cycle, including the role AI can play in target identification, due diligence, and post-merger integration. In the conclusion of this article, to be published in the next issue of The Journal of Robotics, Artificial Intelligence & Law, the author will illustrate the practical applications and benefits of AI as it applies to the M&A deal cycle by providing an overview of M&A transactions that implemented AI tools to improve certain aspects of the M&A deal process. Among other things, the author will discuss the limitations of the use of AI and why, despite the efficiencies gained through the use of AI, human expertise remains crucial for interpreting and evaluating the strength of AI-generated insights, making strategic decisions, and managing complex interpersonal dynamics and efficiencies.
Artificial Intelligence (AI) stands at the forefront of technological innovation, shaping the future of various industries and the ways in which we live and work. AI has made significant strides in recent years, driven by advances in early forms of AI, including machine learning, neural network functionality (initially in hardware, and then in software), and data analytics. These technologies enable AI systems to process vast amounts of data, identify patterns, and make decisions with minimal human intervention.
AI is also revolutionizing the mergers and acquisitions (M&A) industry and is used throughout the entirety of the M&A process for decision-making, risk management, and efficiency. While the results of a 2024 Bain & Company study indicate that only 16 percent of respondents are deploying generative AI in the M&A deal chain cycle today, over 80 percent of respondents plan to use generative AI in the M&A process within the next three years, including to identify, evaluate, and execute acquisitions; provide for a more efficient and seamless integration post-closing; and to drive growth and establish a competitive advantage in general in an ever-changing market.
As AI technologies continue to develop, there will be more opportunities to integrate AI into the M&A deal chain cycle in innovative ways. This two-part article explores the impact of AI on the M&A deal value chain. It begins with a high-level overview of generative AI, discussing recent advancements and applications across various industries. It then delves into how AI is used at different stages of the M&A deal cycle, including the role AI can play in target identification, due diligence, and post-merger integration. In the conclusion of this article, to be published in the next issue of The Journal of Robotics, Artificial Intelligence & Law, this article will illustrate the practical applications and benefits of AI as it applies to the M&A deal cycle through an overview of M&A transactions that implemented AI tools to improve certain aspects of the M&A deal process. The conclusion also will discuss, among other things, the limitations of the use of AI and why, despite the efficiencies gained through the use of AI, human expertise remains crucial for interpreting and evaluating the strength of AI-generated insights, making strategic decisions, and managing complex interpersonal dynamics and efficiencies.
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