The Impact of AI on Mergers and Acquisitions

NORTHAMPTON, MA / ACCESSWIRE / May 13, 2024 / Factors that fall under the umbrellas of both EHS and ESG are vital considerations for organizations undergoing mergers and acquisitions (M&A).

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A Deloitte report revealed that nearly 70% of M&A professionals surveyed consider ESG (environmental, social, and governance) factors to be of "high strategic importance" in their decision-making processes. Additionally, EHS (environmental, health, and safety) considerations are becoming crucial due to legal and financial risks associated with non-compliance.

Still, these high-risk factors may be overlooked during the M&A process for reasons ranging from inadequate frameworks to data availability and quality. Fortunately, new advancements in AI and machine learning are making it easier to discover, gather, and process relevant data.

Let's explore how the mergers and acquisitions field is employing AI solutions to meet the demands of EHS and ESG due diligence, and how this explosive technology will change the work of M&A in the near future.

How AI Is Used in M&A?
AI use in the field of M&A is not as widespread as other sectors - yet. A report by Bain found that only 16% of M&A professionals are employing generative AI today. However, within three years that number is expected to reach 80%. According to the report, "the early adopters are primarily in technology, healthcare, and finance, and they tend to be larger companies with moderate M&A activity of three to five deals per year."

M&A professionals reported a significant reduction in manual effort, with a downstream impact of accelerated timelines and reduced costs.

But AI technology encompasses more than just generative AI. Here are some examples of how AI can improve the integration of EHS and ESG considerations in M&A.

Due diligence
AI tools significantly streamline the EHS and ESG due diligence process by automating the review of large datasets. These tools can swiftly identify potential issues, such as non-compliance with environmental laws, safety violations, or lapses in governance. AI-driven natural language processing (NLP) technologies can analyze unstructured data from various documents, including sustainability reports, safety records, and regulatory filings.