Ask a roomful of contractors where projects go wrong, and very few will say "the drywall." They'll say the contract — a vague scope, a missed notice deadline, an obligation nobody flagged until it was a problem. The data backs that up. Year after year, the leading causes of construction disputes aren't physical; they're documentary: errors and omissions in contract documents, parties not understanding their own obligations, and changes in scope. Scope change alone shows up in roughly a quarter of projects worldwide.
So when I think about where AI can protect a client's budget, I don't start with robots or drones. I start with the paperwork — because that's where the expensive surprises are actually born.
What the numbers really say about change orders
There's a popular figure that change orders eat 10 to 15% of a project's cost. The most rigorous dataset I've seen — an analysis of nearly 900,000 change orders across more than 18,000 completed U.S. projects — puts the typical impact closer to 4 to 5%. That's a healthier number than the scare statistic, and it points to something important: change orders aren't a disaster, they're a normal part of building. What turns a routine change into a dispute is ambiguity — a scope two parties read two different ways, or an obligation that surfaces too late to manage.
That's the problem worth attacking. And it's one AI is genuinely suited to.
Where AI helps: a tireless first read
A new class of tools reads a construction contract or spec the way a careful project manager wishes they had time to — flagging risky provisions, payment terms, notice and deadline requirements, indemnities, and places where the spec and the contract don't agree. The leading construction-specific tool in this space has reportedly been used across more than 10,000 projects and was just acquired by one of the industry's largest technology companies — a sign this isn't a novelty; it's becoming infrastructure.
Used well, it does two things for a client. It compresses a multi-hour contract review into a first pass measured in minutes, and — maybe more valuable — it lets a project manager, not just a lawyer, find the clause that matters before it becomes a change order. Catching a one-sided notice provision or a buried scope gap during review is essentially free. Catching it during a dispute is anything but.
Where it stops — and where my legal training makes me careful
Here's the part most "AI in construction" articles skip. AI is a powerful first reader. It is not a lawyer, and treating it like one is its own kind of risk.
Independent research has found that even purpose-built legal AI tools produce hallucinations — confident, wrong answers — on more than one in six queries, and general chatbots far more often. Courts across the country have sanctioned attorneys for filing briefs with AI-invented case citations. A tool that will fabricate a court case will just as easily misread a flow-down clause. So at DALCORE, AI flags; a human decides; and on anything consequential, a qualified attorney reviews. The model has no accountability for the outcome — we do.
There's also a quieter trap that matters to anyone handling a contract: confidentiality. Paste a sensitive agreement into a public AI tool and you may have, in the eyes of some courts, waived the legal privilege or protection that contract relied on. Two separate federal courts in 2026 landed on opposite sides of exactly this question. The lesson isn't "don't use AI" — it's to use vetted, secured tools and never treat a public chatbot as a safe place for a client's confidential documents. Having spent years on the legal and compliance side of AI companies, I take that seriously, because the downside is irreversible.
The standard we hold
The point of all this isn't to run a contract through a machine and call it diligence. It's to give every project a fast, consistent first read so nothing important hides until it's expensive — and then to put experienced human judgment, and real legal review, exactly where they belong. The best dispute is the one that never happens, because the risk got caught on page nine during review instead of in a claim two years later.
That's how we use AI on the contract side: as an early-warning system, not an authority. It makes us faster and more thorough. It doesn't get to make the call — and it never sees what it shouldn't.
— Anthony D'Alessandro Jr., J.D.