Over the past few months, since starting university, I have been interning at a search fund run by former Valsoft associates. A big part of my role has been sourcing and analyzing hundreds of mission-critical vertical market software companies.
Most of the businesses I looked at were not flashy. Their founders were often old, and their products were the kinds of software/systems that never make Forbes headlines but run entire industries (e.g.,payroll, compliance, emergency wildfire dispatch, and niche billing systems). in the background.
Seeing how dependent these businesses are on their software changed how I think about AI. I don’t believe AI will impact vertical market software the same way it impacts horizontal SaaS.
Where AI Actually Fits in VMS
Vertical market software lives inside highly specialized workflows like construction estimating, healthcare documentation, insurance underwriting, public safety dispatch. These are domain-heavy, compliance-heavy environments that are embedded in daily operations.
AI tends to work best when three conditions are met:
- The workflow is repetitive and expensive
- The data is unstructured
- The cost of errors is high, but clearly defined
Vertical market software checks all three boxes.
Because of this, AI in verticals is not about replacing software. It is about expanding what software can do.
From Systems of Record to Systems of Action
Traditional VMS products are systems of record. Humans do the work first, and the software stores the result.
AI changes that dynamic. VMS becomes a system of action.
Instead of helping a user complete a task, the software completes the task itself.
Examples include:
- Drafting inspection reports from voice notes
- Generating insurance claims from uploaded documents
- Writing clinical notes from patient conversations
- Reviewing contracts and flagging risks automatically
- Handling inbound calls or support tickets without human involvement
This shift fundamentally changes pricing power.
When software replaces labor instead of merely supporting it, pricing moves from per-seat models to per-outcome models: per report, per claim, per case, per ticket. That is how VMS companies move from capturing 2–5 percent of a role’s value to capturing 25–50 percent.
Why Vertical AI Is More Defensible Than It Looks
Vertical markets demand accuracy, compliance, auditability, and predictability. Generic AI tools struggle in those environments.
Vertical AI works because it is trained on domain-specific data and embedded deeply into real workflows. Over time, customer usage generates proprietary data that compounds into a meaningful moat.
This is not about adding an AI wrapper to existing software. It is about building products that understand an industry well enough to operate inside it.
My Takeaway
AI will likely make the best vertical market software companies even stronger. It turns software that tracks work into software that does work, increasing stickiness and value per customer.
But there are real risks. Poorly implemented AI can destroy trust quickly in mission-critical environments. Over-automation can introduce silent errors that only surface when they become expensive. Vendors that rush AI without understanding the domain risk turning stable software into a liability.
The winners will not be the companies that move the fastest. They will be the ones that integrate AI carefully, respect the workflow, and make the product more reliable, not just more exciting.
Across North America, groups like Constellation are already investing heavily in AI, both to improve internal efficiency and to strengthen their portfolio companies’ products. That approach is why I’m bullish on VMS in an AI-driven world, but only for operators who treat AI as infrastructure, not a feature.