Editorial update, October 3, 2026: The PwC attribution and valuation discussion have been revised, with a link to the source report.
Your AI Posture Is Now on the Diligence Checklist
PwC’s January 2026 M&A outlook recommends making AI due diligence part of every deal. It advises buyers to examine the target’s AI plans, likely business effects, resource needs and management’s ability to execute.
For an owner, the practical response is to document how the business uses AI, what results it produces and whether those results can continue under new ownership.
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?
Using AI does not, by itself, establish a valuation premium. Document what the systems do, their costs and risks, and who can operate them. That evidence can inform diligence; it does not establish a standard revenue multiple.
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 practical benefit is a clearer account of how the business works and what it can sustain without you. That is useful preparation whether you plan to sell or keep the company.
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 show that evidence, you are better prepared for diligence. If you cannot, you have a concrete documentation and operating task.
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/