Artificial intelligence (AI) has the potential to revolutionize M&A, significantly reshaping dealmaking and due diligence. This evolving technology is already bringing about greater efficiencies and productivity gains. How is it being used in and impacting the legal sector? And what challenges remain to implementing and utilizing more fully? Jonny Bethell, Tom Hartwright, and Tom Maw sat down with Datastie’s Sam Dormon at the recent Legal500 Corporate and M&A Summit 2025 in London to find out.

Use in due diligence…

In a recent Datasite survey of more than 620 global dealmakers in the US, UK, France and Germany, 66% of global dealmakers said exploring the use of new AI tools is their top area of operational focus in 2025. And one of those areas that it’s being put to use in is due diligence.

Legal due diligence consists of two key elements: gathering and summarizing information and then analyzing it to provide recommendations and insights. The first part is already being streamlined by AI, with tools capable of rapidly extracting and consolidating data. However, adoption has been slower than the technology allows, largely due to trust issues and the need for verification. As these challenges are addressed, AI-driven due diligence is expected to become more widespread, significantly improving efficiency.

Beyond efficiency, AI could expand the scope of due diligence. Historically, firms have relied on sampling because reviewing every contract or financial detail was impractical. AI could change this by cross-referencing customer contracts with creditworthiness databases, company accounts, and other public records, creating a more comprehensive risk analysis than was previously possible.

AI is also poised to improve the early stages of M&A, where dealmakers assess potential targets. By aggregating vast amounts of financial, regulatory, and market data, AI can quickly determine whether an opportunity is viable, saving time and resources.

As trust in AI tools grows, their integration into deal origination, analysis, and decision-making could become standard practice, reshaping how deals are sourced, evaluated, and executed.

…and beyond

But AI is also having an impact in areas beyond due diligence. For instance, AI is transforming legal spend, fee structures, and service delivery, but its impact varies depending on the nature of the work. For high-volume, low-value tasks, AI enables in-house teams to handle work that would have traditionally gone to external firms, reducing costs. However, in complex transactions like M&A, AI is unlikely to significantly cut fees in the short term because clients still value human expertise and legal judgment, particularly on material contracts. So, while AI can streamline certain aspects of the process, such as document review and summarization, the final analysis and decision-making remain firmly in human hands.

AI is also changing how legal services are delivered. Clients may now use AI to generate preliminary analyses before engaging external counsel, altering when and how lawyers are brought into deals. Additionally, AI is shifting fee structures, with firms increasingly asked to offer fixed or semi-fixed pricing rather than billing purely by time. Some firms have even considered charging separately for AI tools, though this is likely to become as standard as software licenses.

Beyond cost savings, AI’s integration into legal practice could make firms more attractive to both clients and talent. More efficient workflows might improve work-life balance for junior lawyers, leading to better retention and stronger client service. In pitches, AI is now a key selling point, but firms must strike a balance—demonstrating its value without overselling capabilities. Ultimately, AI’s greatest impact may not be in reducing costs, but in enabling deeper, more comprehensive analysis that was previously impossible.

Challenges remain

Despite its potential benefits, implementing and utilizing AI in M&A processes still presents significant challenges. One major hurdle is the rapid pace of technological change. Law firms and businesses must carefully decide where to invest their time and resources, as AI tools can become outdated quickly or lose support due to shifting market trends. This unpredictability makes long-term investment in AI solutions difficult, especially in an industry that values stability and reliability.

Another challenge is integrating AI into existing workflows. Firms often use different tools across various practice areas, many of which rely on the same underlying AI models. However, ensuring seamless compatibility between AI tools, data sources, and reporting systems remains a complex issue. On the buy-side, for example, data accessibility is often restricted, making it difficult to feed AI systems with the necessary information. Even when AI tools generate insights, they still require human oversight to contextualize findings and prioritize key risks for specific clients.

Trust and confidentiality are also significant concerns. In fact, when considering the barriers of AI adoption, most dealmakers (34%) have identified data privacy and security concerns as the greatest risk to using AI in their business.

Finally, resistance to change remains a challenge. Many decision-makers are wary of AI due to a lack of understanding or concerns about accuracy. While AI adoption will likely increase as trust builds over time—similar to how cloud storage was once met with skepticism—firms must carefully balance innovation with risk management. As AI continues to evolve, addressing these challenges will be key to unlocking its full potential in M&A.