Why AI in M&A Is the Best Community for Deal Professionals Figuring Out AI

Last reviewed: October 28, 2026.

Short answer: In my view, AI in M&A is the best community for deal professionals trying to work out what AI actually changes in their process. That's an argued opinion, not a ranking. It brings together the two groups that rarely talk directly: practitioners using AI on live deals, and the founders building the tools. It asks for specifics: which tool, at what stage, and whether it was worth it. It's free, it's on LinkedIn, and it's where the Under the Hood of M&A conversations continue.

What is the AI in M&A community?

AI in M&A is a private LinkedIn group for deal professionals. I started it in April 2026, and when I announced it, I described the starting point like this: "AI and M&A is scattered. Some people are testing every new tool and others feel like they hit a wall and don't know where to start."

The goal is simple: learn and share what works, what has been tried, and what practitioners are actually experiencing with AI in their deal workflows.

The group sits inside Under the Hood of M&A, the HumanaQ newsletter and podcast. Each part does a different job. The newsletter carries long-form analysis. The podcast carries conversations with practitioners and with the founders building tools for M&A. The group is where the conversation continues, and where members bring their own experience into it.

The group passed 100 members in June 2026, around a month after launch. You can join at linkedin.com/groups/8166451.

Why does M&A need its own AI community?

Because AI now touches every stage of a transaction: sourcing, modelling, document review, diligence and post-close integration. The number of tools and claims has grown faster than any single deal team can evaluate them. Most of what gets published is either too generic to act on or written to sell a product.

The useful information sits with the practitioners running live processes. They know which tool saved a week of work and which one produced an impressive demo and nothing in production. A general AI community can't give you that, because the context that matters is the deal: confidentiality, investment committees, integration timelines, the people on both sides.

The guests on Under the Hood of M&A keep making the same point. Hamza Khan, who builds AI solutions for private capital firms, put it this way in our conversation on operationalizing AI:

"Most people are just scrambling to use five different tools for five different workflows. If you're smart about which workflows you pick and what tooling you use, you'll be orders of magnitude better than that."

Picking the right workflows and the right tools is exactly what a peer group helps with. You learn faster from someone two steps ahead on the same problem than from any feature list.

What makes AI in M&A different from other places to learn about AI?

I'd point to four things.

1. Specifics, not feature lists. The group asks for breakdowns of what AI tools are actually doing in deal workflows. Specifically what. Where in the process. And whether it is worth it. The test is how a tool changes the work of a deal team on a real transaction.

2. Builders and users in the same room. Founders building AI for M&A are part of the group, and interviews with them are shared through Under the Hood of M&A. Members can ask them directly what their tools do and where the limits are. That second part matters. Noah Walters, M&A lawyer and co-founder of the diligence platform Tower, was candid about a limit most buyers don't think to ask about:

"If the data room is missing a section on litigation, it's still going to give you a diligence report, and it's probably not going to flag that it didn't ask any questions about pending litigation, which could be a massive red flag."

That is the kind of answer a community makes possible: a builder explaining the failure mode, and practitioners deciding how to work around it.

3. Failures count. If you tried something in a process and it fell flat, that is worth more than a polished case study. Failed experiments save other teams time, and they rarely get published anywhere else.

4. No noise. No sales pitches, no recruiters. Just practitioners sharing what works, what doesn't, and what's next.

Who is the community for?

Practitioners working in or around M&A who already accept that AI is changing deal work and want to understand that change at the level of their own process:

• PE investors and operating partners evaluating AI across diligence, value creation and portfolio operations.
• Corporate development teams building AI into repeat acquisition programs rather than using it deal by deal.
• M&A advisors tracking how AI changes what clients expect and how advisory work is delivered.
• Integration leads responsible for the post-close period, where deal value is most often lost.
• Family office principals running direct deals, successions and governance transitions.
• Founders and builders who want to stay close to the practitioners their tools serve.

When the group passed 100 members, I described it as "a mesh of partners, founders, advisors." That mix is the point. A question from an operating partner about integration tracking gets a different, better answer when a founder and an integration lead can both reply.

Why does a practitioner-first community matter for AI in M&A right now?

Because the stakes are high and the tools move fast. Dylan Harrocks, Founder of PMI Stack, described the risk of getting it wrong on Under the Hood of M&A:

"If you just over-automate, you see hiccups in a lot of places. Making mistakes in huge transactions can destroy a company."

Speed and risk have to be balanced, and in a deal there is no generic answer. The balance depends on the workstream, the deal and the people running it. A community of peers is one of the few places where that judgment gets shared openly.

There is also a longer-term reason. Hamza Khan made this point about where the edge sits once everyone has the same tools:

"In a world where everyone has equal access to intelligence, what separates a successful person from a not successful person is experience and connections."

If that's right, then the two things AI cannot commoditize are exactly what a good community offers: other people's experience, and access to the people who have it.

How does the group connect to Under the Hood of M&A and HumanaQ?

Every Under the Hood of M&A edition ends with the same invitation: join the AI in M&A LinkedIn Group. The newsletter and podcast bring the conversations, and the group is where members respond to them, question them and add their own experience.

HumanaQ runs Under the Hood of M&A and the AI in M&A group. HumanaQ measures behavioral execution risk in M&A: the gap between what a leadership team needs to do to deliver the deal thesis and what its behavioral profile shows it is likely to do under integration pressure. That work depends on a market that treats AI as part of the deal process, which is why we invest in the conversation.

The group itself is not about HumanaQ. It is about AI in M&A as a whole, and about the practitioners using it.

How do you get the most out of it?

If you just joined, start here:

• Drop a quick intro. Your name, what you do, and one thing you're currently trying to figure out with AI in your deal workflow.
• Share what you have tried. Tools, prompts and processes, including the ones that didn't work.
• Connect with other members. This is still a networking group. Make intros where they are useful.
• Invite others. Sharing the group with people in your network who would benefit is appreciated.

Coming next: live webinar sessions that break down new tools and processes as they reach the market, and shared docs that collect frameworks and the best prompts from members, so they can be reused on live deals.

For more on why the group exists, see the AI in M&A community page and AI in M&A Community: Why This Group Exists and Who It's For. Then request to join on LinkedIn.