Your AI Posture Is Now on the Diligence Checklist
PwC published their 2026 global M&A outlook last week.
Buried inside it between the usual slides about multiples and market conditions was something that should stop every operator in their tracks.
AI diligence is now a standard line item in deal underwriting.
Not a nice-to-have. Not a bonus question if the buyer happens to be tech-savvy. A standard. Acquirers are now expected to assess your AI strategy, estimate its business impact over the next three to five years, evaluate capital requirements, and this is the one that matters most test whether your management team can actually execute on it.
That last part is the tell. Because most operators can't answer it. Not because they're behind. Because they've never been asked before.
You're about to be asked.
What "AI Readiness" Actually Means in a Deal Room
Let me translate the consultant language into plain English.
When a buyer asks about your AI posture, they are not asking whether you use Chat GPT. They're asking a more uncomfortable question: Is this business operating on infrastructure that compounds over time, or is it running on the same tribal knowledge and gut-call decisions it was running on five years ago?
AI is just the current lens. The underlying question has always been the same: What happens to this business when the owner leaves the room?
The PwC data says acquirers are willing to pay 8 to 15 times ARR for lower middle market companies with proven agentic capabilities and proprietary data moats. That premium over non-AI comparables isn't about technology; it's about certainty. Certainty that the business has durable systems underneath it. Certainty that what the business knows doesn't walk out the door.
An 8–15x ARR premium in the lower middle market is not a rounding error. That's the difference between a number you're proud of and a number you're explaining to your spouse.
The Gap Nobody Is Talking About
Here's what I'm seeing in the market right now:
Operators are adopting AI tactically. A tool here, an automation there. Time saved on emails. Faster proposals. Maybe a chatbot on the website.
None of that shows up in diligence.
What shows up in diligence is whether you can answer three questions with documentation:
1. What AI systems does this business use, and what decisions do they inform? Most owners can list the tools. Almost none can show the decision logic.
2. How does your AI posture reduce key-person dependency? This is the owner dependency question in a new costume. If the answer is "we use AI to help me do my job faster" — that's not what the buyer wants to hear. That's still owner-dependent. The system that runs faster when you're in the room is not the same as the system that runs the same when you're not.
3. What's your data moat? What proprietary operational data have you accumulated that makes your business harder to replicate? Most small operators don't think they have one. Most of them are wrong. They just haven't inventoried it. If you can't answer these off the top of your head with some evidence behind them, you don't have an AI readiness problem. You have a documentation problem. Which is fixable.
Why This Matters Even If You're Not Selling
I hear this every time I talk to an operator. "Steve, I'm not planning to sell. "Okay. Fair enough".
But consider what a business looks like when it can answer those three questions clearly:
- Decisions are documented. Process over person.
- Systems produce consistent output regardless of who's in the room.
- The business accumulates institutional knowledge instead of losing it when people leave.
That's not an exit-ready business. That's just a well-run business. The AI readiness framework is just the current vocabulary for something operators have needed for decades.
The difference is that buyers are now putting a number on it. And you should too whether you're selling or not.
Where to Start
You don't need an AI strategy deck. You need an honest inventory.
Start here
Audit what you're already doing. Most operators are using more AI than they realize, just not systematically. Catalog every tool, every automation, every decision that's been removed from the gut-feel column and put into a system. That's your baseline.
Identify your data. What operational data does your business generate that competitors don't have? Customer behavior patterns, production variance data, supplier performance history, margin by job type. These are data moats. Write them down.
Map your key-person dependencies. Where does critical knowledge still live only in someone's head? Those are the gaps a buyer will find. Better to find them first.
Score it. Not with a consultant's framework. With your own honest assessment. Can I walk into a buyer meeting and demonstrate, with evidence, that this business has an AI posture — not because I installed tools, but because my systems think?
If you can, you're in the premium tier. If you can't, you have a concrete project.
The Uncomfortable Truth
AI is now a valuation factor. That's the headline. But the real story is older than AI.
Businesses that run on systems are worth more than businesses that run on people. Buyers have always known this. They're just using new vocabulary to measure it.
The operators who get ahead of this question, who can walk into a room and say here's our AI posture, here's our data, here's our score aren't just better positioned for a transaction. They're running better businesses.
The others will find out what they missed on the day the LOI comes in light.
You choose the conversation you want to have
Steve Duke is the founder of Lucensys™ Group, an advisory firm helping manufacturing, distribution, and construction owners scale their businesses, reduce owner dependency, and build enterprise value. He works with companies doing $2M–$50M in revenue. Want to know your current AI readiness score?
Book a Clarity Call https://zoomwiththeduke.com/