While AI is still in its early stages within the M&A sector, its potential to transform dealmaking and due diligence is evident.  Patrick Sarch, Head of UK Public M&A at White & Case, and Merlin Piscitelli. CRO, EMEA at Datasite, recently discussed the trends and challenges of utilizing AI in M&A, including how this evolving technology is expected to bring about greater efficiencies and productivity gains, ultimately reshaping the landscape of M&A transactions.

AI in M&A: Where Are We Now?

Despite the rapid advancements of AI in other fields, its application in M&A is still in its infancy. Many industry professionals are intrigued by AI’s potential but have yet to see its full benefits. Datasite recently found that 36% of dealmakers cited data security and privacy as the primary concerns in using AI tools. Additionally, 73% felt that AI in M&A should be more regulated. In other words, while interest is high, so is caution.

Productivity Gains

As such, it’s no surprise that M&A professionals appear more likely to accept AI when introduced in small, manageable steps rather than sudden, sweeping changes. Incremental enhancements can drive meaningful improvements in productivity without requiring a radical shift. Younger generations, accustomed to AI in their personal lives, are often the early adopters, driving demand for mobile-friendly tools and AI-based solutions in dealmaking.

Document categorization and redaction are two areas where AI is making significant inroads. Traditionally, M&A professionals and lawyers spent countless hours sorting documents and manually redacting sensitive information, a process often fraught with errors. AI-powered document categorization tools can quickly sift through thousands of pages, suggesting where each document should be placed within the data room.

At Datasite, AI is already improving document management by increasing the speed and accuracy with which documents are ingested and categorized. In fact, Datasite has seen a 32% increase over last year in the number of documents handled in its data rooms, much of which can be attributed to AI’s ability to process and organize vast amounts of information. This allows M&A professionals to focus on analysis rather than the laborious task of document sorting.

Business Development and Buyer Identification

Another promising use case for AI is in identifying potential buyers. AI search engines can access various data sources, such as public registries, to identify potential acquirers or partners who may not have been considered otherwise. By leveraging AI to build buyer lists, firms can enhance their business development efforts and uncover opportunities that may have otherwise been missed. This ability to generate insights from vast data sources is particularly valuable in a competitive market where dealmakers aim to maximize value for their clients.

Challenge of Widespread AI Adoption

One of the key challenges AI faces in the M&A space is the hesitancy of some organizations to open their data to external AI tools, primarily due to security concerns. Many sellers, for instance, are reluctant to allow buyers or other third-party participants to use AI tools on sensitive data within data rooms. This reluctance is due to a lack of control once data leaves the secure environment of the data room and enters third-party AI platforms. There is also apprehension that sensitive information might leak into the market, creating additional risks. Consequently, much of the AI development and adoption seen in M&A today remains internal, focused on improving efficiency within controlled environments.

A Look Ahead: AI’s Role in M&A Over the Next Five Years

Looking to the future, AI is expected to play a significant role in reshaping due diligence processes. While today’s AI can assist with document categorization and basic analysis, there is hope that in five years AI will be able to analyze vast quantities of data independently, highlighting key areas of risk and opportunity. Rather than reading hundreds of thousands of pages, M&A professionals could rely on AI to summarize essential information and flag areas requiring deeper analysis.

This shift will allow experts to focus on high-level strategic decisions rather than the initial stages of due diligence, reducing the time needed to complete transactions and potentially cutting costs. However, this future vision of AI in dealmaking can only materialize if the industry overcomes its resistance to change. The expertise of senior dealmakers will need to be augmented, not replaced, with AI, and organizations will need to foster a culture of openness to new technologies.