By John Cohan and Zane Fernandez
Artificial intelligence (AI) has become an increasingly important tool for businesses in recent years. In fact, a 2023 OnePoll study notes that 64% of U.S. business owners anticipate that AI will improve customer relationships and increase productivity, and 60% expect AI to drive sales growth. Companies are now using AI to automate tasks, analyze data, and make decisions. As a result, AI is having a significant impact on corporate mergers and acquisitions (M&A). In this article, we will explore the ways in which AI is affecting the M&A landscape and what this means for businesses.
It is critical to understand the ways that AI can assist professionals with responsibly streamlining the M&A process particularly because research shows that M&A transactions are significantly increasing in both volume and complexity. For instance, a study by Gartner shows the average time to finalize an M&A deal has increased by 31% in the past decade alone. Notably, closing dates have prolonged even more for midsize to larger deals ($500 million to $5 billion), which takes an average of 106 days to close. Gartner explains that this trend results from “a rise in deals for scope and capabilities, digitally-driven deals, and cross-border deals.” Moreover, “growing scrutiny from governments, regulators, and investors [has] also contributed,” Gartner notes. With this context in mind, the benefits of AI become even more apparent with its capabilities to potentially make the M&A process more efficient and cost effective while also reducing human error.
One of the most significant impacts of AI on M&A is in the due diligence process. Due diligence is the process by which an acquiror investigates a target before a merger or acquisition. This process is critical because it helps the acquiror understand the risks and opportunities associated with the target. Traditionally, due diligence has been a time-consuming and labor-intensive process that involves humans reviewing large amounts of data and documents. However, with the help of AI, due diligence can now be substantially streamlined and accomplished more quickly and efficiently.
AI can analyze large amounts of data and identify patterns and trends at high speeds and with accuracy that outperform even the most efficient human analysts. AI can rapidly analyze financial data to identify potential red flags, such as unusual expenses or revenue recognition practices, as well as customer data to identify trends in customer behavior and preferences. By using AI to conduct due diligence, acquirors can save significant time and money while also getting a more comprehensive understanding of the target.
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Identifying Acquisition Targets
AI can also assist companies with identifying potential acquisition targets. Traditionally, companies have relied on human analysts to identify potential targets based on factors such as industry, size, and financial performance. However, given AI’s current level of sophistication, it can now be used to identify potential targets based on more complex criteria, such as customer behavior, market trends, and social media activity. By using AI to identify potential targets, companies can find more meaningful and focused opportunities that may otherwise be overlooked by human analysts.
AI has become a critical tool used to assess the valuation of companies in M&A. Traditionally, valuation has been based on financial metrics such as revenue, profit, and cash flow. However, AI can now be used to analyze non-financial data, such as customer behavior and social media activity, which can provide a more comprehensive view of a company’s value. By using AI to analyze non-financial data, companies can get a more accurate valuation of the target company and make more informed decisions about whether to proceed with the acquisition.
Additionally, AI is impacting M&A by helping companies integrate the target company after the acquisition transaction. Integrating two companies can be a complex and challenging process, but AI has the potential to make it a more seamless transition. For instance, AI can be used to analyze the data from both companies and identify areas of overlap and potential synergies. By identifying these areas, companies can more effectively integrate the two companies and achieve the desired synergies.
AI is continually changing the competitive landscape. As companies continue to adopt AI, they are becoming more efficient and effective, which means they can compete more effectively with other companies. This is particularly true in industries where AI can provide a significant competitive advantage, such as healthcare, finance, and retail thereby making them more attractive to potential suitors. As a result, companies that are slow to adopt AI may find themselves at a disadvantage when it comes to M&A.
Of course it is important to consider some of the potential risks that could result from the use of AI in the M&A process. For one, who should be liable in the event an AI program somehow inaccurately evaluates diligence documents? To offset this risk, law firms ought to find ways to manage such potential liability between themselves and their third-party AI providers. There could also be data security and confidentiality risks in the event of a data breach of an AI program that results in disclosure of confidential information.
Legal and ethical risks could arise from algorithmic biases in evaluating companies that may lead to discrimination or unfair practices. Despite such risks, AI has become even more common in the M&A process, and it will continue to grow. Thus, it is best to think strategically about the potential risks, and eventually, as demand increases, more solutions to manage such risk will likely become available.