AI leverage is the new deal currency for PEs

When Connor O’Hearn first started experimenting with GPT-3 in 2022, AI felt like a playground for software engineers and not something that belonged in an M&A process. 

“Developers were the early adopters,” he recalls. “Meanwhile, lower-middle-market deal teams were just too busy to keep up.”

Fast forward to 2025, and O’Hearn’s firm, Maai Services, is now helping private equity funds, VCs, family offices and law firms to bring AI into every stage of the deal lifecycle. 

We sat down with him on the Clause and Effect podcast to explore where AI really delivers value, why smaller firms are leading the way, and how today’s PE analysts can use AI to level up faster than ever before.

What AI actually unlocks in M&A workflows

At its core, AI isn’t magic. It’s leverage. O’Hearn breaks its value into three categories:

Three places to start with AI

These aren’t theoretical use cases; they’re the entry points Connor sees delivering real impact in firms today. Start here, build momentum, and let the results speak for themselves.

1. Legal due diligence
   Tools like Emma automatically label, sort, and summarize thousands of documents against your checklist. “It’s like starting the review at 20 miles per hour instead of zero,” says O’Hearn.
   
   
2. Sourcing intelligence
   Imagine pulling fragmented deal notes from calendars, emails, and slide decks into one searchable AI assistant. Suddenly, that cold lead from last quarter might be worth a second look.
   
   
3. Portfolio insight
   Use AI to scan board updates, dashboards, and customer notes to catch signals early before problems get buried or opportunities get missed.
   
   

So why hasn’t everyone adopted this?

O’Hearn sees three common blockers:

• Change aversion – “I’ve been doing deals this way for 20 years” still dominates many rooms.
• Wait-and-see mindset – Most firms would rather let someone else go first.
• Security concerns – Uploading sensitive docs into a chatbot is a non-starter unless the tools prove SOC 2 and GDPR compliance (as Emma does).

His take? Start small. Run a low-risk pilot. Once the time savings are visible, momentum builds on its own.

Why the smallest firms are moving fastest

It’s not the big firms leading the charge, it’s the lean ones.

“These three-to-five-person teams don’t have time to waste,” O’Hearn says. “AI gives them the leverage to move faster, make smarter decisions, and play on a much bigger field.”

And LPs are noticing. More and more fund managers are getting asked, “How are you implementing AI?”

AI is flattening the career ladder

Traditionally, climbing the ladder in private equity or law meant 20+ years of grunt work. But AI is changing that.

The new advantage? Being AI-bilingual.

“You still need to know how to build a model or write a memo,” O’Hearn says. “But if you can also prompt, build simple workflows, and identify automation opportunities, you can shortcut the grind.”

He encourages junior analysts to pilot tools internally and champion small wins. “Be the one who brings a solution. That’s how you stand out.”

More orchestration and agents

O’Hearn points to something bigger than just smarter chatbots, but orchestrated systems where AI tools connect with legacy software, passing information and decisions back and forth automatically.

Think:

• AI that updates valuation models with fresh data
• Board decks generated overnight from raw metrics and commentary

“That’s the vision,” he says. “Not just chatbots, but workflows that actually work together.”

Efficiency is just the beginning

Many teams think of AI as a time-saver. And it is. But O’Hearn says that’s only the first layer of value.

“Yes, you save time. But you also make better decisions because you’re working with cleaner data, clearer insights, and fewer blind spots, all on compressed timelines.”

That matters in M&A, where velocity is critical.

Final thoughts on how to bring AI into M&A

O’Hearn recommends a four-step approach:

1. Start with curiosity: Play with it. Ask questions. Learn what’s possible.
2. Find the low-hanging fruit: Target repetitive, high-effort workflows.
3. Scale what works: Codify it, and roll it out across teams.
4. Go beyond efficiency: Use the time you save to elevate quality, strategy, and creativity.

“Don’t just chase speed,” he says. “Chase insight. That’s where the future is.”

And in a world where the smallest funds are already thinking like giants, the real edge is no longer size, it’s leverage.