AI in M&A: Built In or Bolted On?

Artificial intelligence (AI) is increasingly being integrated across mergers and acquisitions (M&A) workflows to help deal teams reduce manual work, find answers faster and make more informed decisions. With so many virtual data room (VDR) and dealmaking platforms now describing themselves as "AI-powered," it’s become harder for deal teams to tell what that actually means in practice. The key question is not simply whether a platform offers AI, but how deeply that AI is built into the deal process.

That distinction matters. AI added to an existing product may offer useful features, but it can also leave teams to work out how and where to use them. Purpose-built AI takes a different approach. It brings intelligence directly into the workflows deal teams already rely on, automating manual steps while giving users the accuracy, transparency and control high-stakes transactions demand. The real test is whether the technology saves time while helping teams to maintain confidence in the results.

AI should simplify the workflow

Giving deal teams access to a powerful, open-ended AI tool doesn’t necessarily make their work easier. When users have to determine how to use it, build processes around it or recreate prompts for routine tasks, AI can add another layer of work instead of reducing it.

That challenge also makes consistency harder to achieve. Without AI embedded into established workflows, deal teams may spend valuable time figuring out how to apply the tool to the task at hand. Different users may approach the same task in different ways. Unfortunately, this means useful prompts and approaches may stay with individual users rather than being shared and standardized across the team. Instead of simplifying the transaction, teams can end up spending valuable time figuring out how to get the most from the technology.

Purpose-built AI works differently. When the intelligence is embedded in established deal workflows, teams can use it where the work already happens. Rather than requiring users to build separate agents or redesign their process around a new tool, AI can help automate familiar tasks and make proven approaches easier to repeat across transactions.

Verifiable answers matter as much as fast ones

For deal teams, speed is only useful when it comes with confidence. When querying deal documents, users need to know the answer and where it came from. Yet some AI tools respond without clear citations or source links, making the information harder to verify.

In a transaction, that is more than an inconvenience. When answers cannot be traced to their sources, teams may need to manually recheck documents before relying on the results. That adds review time back into the process and limits the efficiency AI is meant to deliver.

AI designed for high-stakes dealmaking should make answers easy to verify. Responses should include:

• A link to the source document
• A direct link to the relevant page
• Text that identifies the supporting information on that page

That keeps the dealmaker in control. Users can quickly review the source and validate an AI-generated answer before relying on it. 

Where AI can make a difference across the deal

The value of AI becomes clearer when it supports the work deal teams already do throughout a transaction. That can include categorizing and summarizing documents, identifying and redacting sensitive information, streamlining Q&A and surfacing relevant information on demand — all within the deal environment.

AI should support teams across the deal life cycle and beyond. Operating within a consistent security and governance framework helps teams maintain continuity from preparation through closing. When knowledge, prompts and proven ways of working can be retained and reused across deals, teams do not have to start from scratch each time. Over time, that can turn individual deal experience into institutional knowledge the broader organization can apply.

The questions deal teams should be asking

As AI becomes more common in M&A, simply offering AI is no longer enough to stand out. What matters is how well it supports the way deals get done. When evaluating a platform, deal teams should ask:

• Is AI built into the workflow or is it something users must learn and manage separately?
• Can answers be traced back to a verifiable source?
• Does the technology support the full deal life cycle, or only isolated tasks?

DealCentre AI™, powered by Link, our proprietary AI engine, brings AI-powered capabilities into workflows across deal preparation, marketing, diligence and execution. It is designed to help teams reduce manual effort, find and verify information faster, and apply more consistent ways of working across transactions.

AI should make dealmaking easier, not give teams another technology project to manage. Its value comes down to how well it fits the workflow and how much time it gives dealmakers back to focus on the deal.