Maximizing AI in M&A: Why Dealmakers Must Take a Proactive Role
Dealmakers are quickly recognizing how AI can streamline and transform M&A deal processes. However, leveraging its true value requires thoughtful implementation and human oversight.
Artificial intelligence (AI) is no longer a vision of the future for mergers and acquisitions (M&A) dealmakers — it’s reshaping every facet of the process. Tools like SS&C Intralinks DealCentre AITM are already proving AI’s usefulness in automating workflows and analyzing large amounts of content. With efficiencies and competitive advantages to be gained in a complex and fast-moving environment, the question isn’t if AI will transform the deal lifecycle, but how quickly and effectively firms will adopt it.
Firms that approach this technology with care and precision stand to gain a true competitive edge throughout the deal lifecycle. However, unlocking AI’s potential requires balancing automation with human expertise. Dealmakers must recognize AI’s capabilities and its limitations to integrate it strategically.
This blog, the second installment of our M&AI series (read my first blog, “How AI Will Transform M&A Dealmaking,” here), explores the benefits and potential challenges associated with using AI in M&A, so dealmakers can maximize its effectiveness.
How AI enhances M&A processes
AI is revolutionizing M&A workflows by alleviating manual tasks, accelerating due diligence and enabling more informed decision-making.
Automating tedious tasks
M&A deal teams spend significant time on repetitive administrative work during diligence — uploading files, organizing virtual data rooms (VDRs) and reviewing key documents. It’s important, necessary work that validates the deal thesis by mitigating risk. AI-powered tools streamline these processes by automatically categorizing documents, extracting relevant data and identifying what’s missing. As a result, teams can focus more on strategic analysis, relationship building and higher-level decision-making.
Improving due diligence efficiency
AI accelerates due diligence by detecting missing or incomplete documents, flagging inconsistencies and helping users locate specific content within VDRs. With AI-driven insights, dealmakers are alerted about potential risks, reducing delays and ensuring a more comprehensive review.
Reducing errors and enhancing security
AI’s ability to detect inconsistencies and errors — such as unsupported file formats or restricted documents — helps mitigate risk early in the process. Additionally, AI systems with built-in security measures like “ringfencing” ensure data integrity by only analyzing approved content. Limiting the scope to deal-specific data minimizes the risk of inaccurate outputs and maintains confidentiality throughout the deal lifecycle.
Challenges of AI adoption in M&A
Despite its advantages, AI presents challenges that firms must address to ensure successful and reliable integration into deal processes.
Navigating the learning curve
Generative AI platforms rely on user input, particularly when models function on prompts or queries. Poorly structured prompts or unclear questions can yield incomplete or irrelevant results. This underscores the need to develop strong AI interaction skills to enhance AI’s accuracy and maximize its effectiveness in dealmaking.
Managing unpredictable outputs
Unlike traditional software, which delivers consistent and repeatable results, AI systems are inherently non-deterministic. Outputs can vary slightly each time, depending on available data and contextual nuances. This flexibility mirrors human reasoning but can frustrate users accustomed to rigid, predictable outputs. AI should be viewed as a dynamic assistant — not a flawless oracle. In high-stakes decision-making, human oversight remains critical to interpreting results and ensuring accuracy.
Measuring AI’s performance
Evaluating AI-generated insights can be subjective, making it challenging to establish clear benchmarks for success. This subjectivity makes it harder to quantify performance and reinforce learning within AI systems. Implementing structured feedback mechanisms — such as simple rating systems or qualitative input options — can help refine AI models over time.
The role of human oversight
AI is a powerful collaboration tool, but human judgment remains essential in interpreting nuanced deal details, managing relationships and making final decisions. Success ultimately hinges on strategic implementation, proper training and a balanced approach that keeps human expertise at the core. When thoughtfully integrated, AI can enhance and streamline dealmaking while ensuring trust, security and informed decision-making.
Here at Intralinks, we’re constantly exploring new ways to power complex transactions with secure, purpose-built AI tools. We’re fostering ongoing conversation around AI implementation, so dealmakers can leverage the technology effectively. Until the next installment of the M&AI series, I invite you to check out my previous FAQ blog, where I discuss how Intralinks’ proprietary AI models are designed with a security-first approach to protect sensitive data and the integrity of transactions.