How PE and corporate development teams are unlocking value with AI for M&A.

Corporate development and private equity teams are learning that when it comes to AI, speed isn’t everything. An even greater benefit is the ability to make better-informed decisions before committing time, capital, and leadership attention.

Client-side dealmakers have notoriously huge workloads; AI helps them do it all faster. Right? Well, not quite.

If it were that simple, we’d see AI adoption smoothly distributed across the whole deal process. But that isn’t what’s happening. AI adoption is concentrating in specific stages of the dealmaking journey, according to the latest report from Datasite in collaboration with FT Longitude: The new deal team: What 1,000 dealmakers reveal about AI-driven M&A. These are the junctions where the pressure is greatest: finding the right opportunities, evaluating them quickly, and identifying risks, all ahead of the need to make those critical investment decisions.

AI is often described as a productivity tool. But a far bigger benefit, for corp dev or PE teams, is to help focus their attention and efforts where they matter most.

Heavy lifting vs smarter sifting

Two rival treasure-seekers are racing to find buried gold. One opts for a mechanical digger, to find the loot by brute force. The other brings a metal detector – and a treasure map.

Both approaches might yield results, but it’s clear which one is more efficient. There’s a popular perception of AI being like the mechanical digger, shifting vast quantities of material. Deal teams are now waking up to its smarter applications.

There’s no shortage of opportunities for these teams. What they lack is the capacity to sift them all. More opportunities result in more evaluation time, more information processing, more reporting to leadership – and more false starts. With growing numbers of competitors chasing the same assets, it does get as frenetic as a gold rush.

So, it’s no surprise that AI use is focused on these hotspots: reviewing the hundreds of targets, coordinating multiple diligence workstreams, and preparing investment recommendations, all so the team can catch not just the next opportunity, but the right one.

The report finds that, among both corp dev and PE teams, AI use is highest during due diligence and sourcing. In other words: the two stages where information volume is highest and time is shortest. 

Is speed important here? Absolutely, but it’s the secondary concern. The core goal is to extract meaningful insights from the data that can underpin confident decisions.

Opportunity chaos? How dealmakers can chase fewer false trails

Even more valuable than digging faster is wasting less effort digging in the wrong places. Rather than find more targets, overwhelmed deal teams may need more help eliminating the wrong ones.

Opportunity cost is the specter haunting every prospective deal. Every hour spent chasing a dud opportunity allows a stronger candidate to slip further away.

AI can prevent that. By rapidly analyzing the mountains of market intelligence, teams can trade longer lists for stronger leads. Whether corp dev or PE, they can prioritize targets that genuinely fit their acquisition strategy before committing to intensive research or squandering management’s time.

And this is exactly where dealmakers expect AI to deliver its greatest value in the near future, according to the report. Managing greater deal volume is seen as the single biggest benefit of using AI during the sourcing and screening phases. In a world where data overload can lead to ‘analysis paralysis,’ AI can break the deadlock by offering clearer direction.

Better decisions through deeper diligence

Just as the goal of sourcing and screening is to discover which opportunities deserve attention, diligence confirms which deserve investment. Here, too, AI is changing the economics of decision-making.

Reviewing thousands of pages for issues that could affect valuation or integration, or sink the whole deal, can now be achieved in a fraction of the time. With AI to highlight potential red flags, identify information gaps, and explain technical language, human reviewers can home in on what matters. Even more importantly, they can devote more effort to evaluating what it actually means.

The report reflects this shift. Due diligence consistently ranks among the areas where both corp dev and PE teams see the greatest return from AI.

The key point to note here is that the humans are still at the heart of the process. Arguably, even more so than before. Now it’s their judgment, rather than just their scrolling-hand, that’s being exercised.

A question of confidence

One of the most interesting findings in the research concerns the Q&A process in due diligence. More than half of client-side dealmakers say AI is improving their ability to answer buyer questions at scale. 

On the face of it, this sounds like another simple efficiency gain. In reality, it runs deeper. Every deal involves dozens of queries, document requests, approvals, and follow-ups. Humans on their own will struggle with the volumes of scattered data.

AI can keep all of this information flow together. Duplicate questions can be instantly identified, inconsistencies and contradictions flagged, source documents linked, and fragmented information collated in its proper places. A picture emerges from the puzzle pieces that everyone can agree on. Now, critical decisions can be made with greater confidence than ever before.

Trust is the make-or-break

The key difference between humans and AI is accountability. Even if an AI is doing much of the work, the buck always stops with a human being.

Again and again, the research makes it clear: accuracy and security are the two paramount attributes that dealmakers insist on, if they are to use AI on deals. And however helpful AI may be along the way, the final decisions must always be human-led.

AI is extraordinarily effective at analyzing information, but only humans can be responsible for judging its true significance.

From routine automation to richer information

One of the most encouraging messages from the research is that AI adoption is becoming increasingly strategic. Initially, there was excitement that routine tasks could be automated, but that was just scratching the surface. Today's leading organizations are thinking much more broadly. Now they’re asking:

• How do we evaluate more opportunities without adding headcount?
• How do we identify risks earlier?
• How do we give leadership better visibility across active deals?
• How do we turn faster analysis into better investment decisions?

These are questions of strategy, not technology, and they explain why AI adoption gravitates towards sourcing and diligence. These are the moments when better information has the greatest influence over what happens next.

Datasite is now bringing those capabilities into the secure workflows where client-side deal teams already operate: sourcing, diligence, Q&A, reporting, and governance. All of which help teams make better decisions inside the systems that already support their most sensitive transactions.

In the end, it’s about the metal detector and the map versus the crude mechanical digger. It’s helping dealmakers ignore the wrong work sooner, to minimize wasted effort and opportunity cost, and nail those crucial decisions that generate real value.