Every BI vendor has bolted a chatbot onto their platform. The pitch is the same: ask questions in plain English, get answers instantly.
And yet, executives keep telling me the same thing. They ask a question, get a number, and then... they're right back where they started. They still have to investigate. They still have to figure out what that number means.
The AI gave them an answer. But it didn't give them understanding.
Here's the problem: generic AI doesn't know your business.
Data Access Isn't Business Understanding
Connecting AI to your data is table stakes. What's hard is building AI that understands what it's looking at.
When an operations leader asks "Why is this location underperforming?" – they're not looking for a chart. They want to know: Which customer segments are driving the change? Is it transaction volume or transaction value? Which product categories are affected? When did this start? Are similar locations showing the same pattern?
Generic AI can't answer those questions. It doesn't know which variables matter in your business. It doesn't understand how your metrics relate to each other. It doesn't know which patterns are normal and which ones signal real problems.
It gives you a number. Then you investigate for two hours.
What "Knowing Your Business" Actually Means
Your best executives have spent years building mental models of how your operation works. They know what to look for when something's off. They know which metrics to check first, which combinations of factors explain a problem, which thresholds separate "normal variance" from "needs attention."
When they see a number that doesn't look right, they investigate. They check customer segments. They look at category mix. They compare cohorts over time. They examine patterns across locations. They're testing hypotheses, looking for the combination of factors that explains what's happening.
That expertise doesn't scale. Your senior people can't review every location every day. And when they leave, that institutional knowledge walks out the door.
Generic AI doesn't solve this. It doesn't have your executives' mental models. It just answers whatever question you ask – and you have to already know the right question.
Domain Intelligence: Your Expertise, Encoded and Scaled
We built Domain Intelligence around a simple insight: the expertise already exists in your organization. The challenge is capturing it and scaling it.
It starts with a configuration session where we sit down with your executives and encode how they think. What do they look for when a location underperforms? What triggers concern? What patterns usually explain problems? What thresholds matter?
We're not building generic playbooks. We're capturing the specific mental models your people have developed over years in your business. The definitions that aren't in any textbook. The investigation patterns that come from experience.
Then that expertise runs across your entire operation, continuously.
It Keeps Learning
But here's what makes this powerful: Domain Intelligence doesn't stop at that initial configuration.
As your team uses the system, it learns. When an investigation surfaces something and you tell it "that's not quite right" or "this is what I was actually looking for" – it incorporates that feedback. The patterns refine. The thresholds adjust. The system gets smarter about your specific business over time.
Investigations that take longer at first get faster as the system learns your patterns. It starts to recognize what matters to you and what doesn't. It learns your language, your definitions, your priorities.
This isn't a one-time setup that goes stale. It's a system that evolves with your business, continuously getting better at thinking the way your best people think.
The Difference in Practice
With traditional BI or generic AI, you ask "Why did revenue decline?" and get: "Revenue decreased 18%." Maybe a chart. Maybe a breakdown by one dimension.
Then you start the real work. You check customer segments. You look at categories. You examine transaction patterns. You compare to similar locations. You're testing hypotheses one at a time.
With Domain Intelligence, you get the investigation itself. The system has already analyzed which segments are driving the change. It's already found which categories are affected. It's already checked the timeline. It's already compared to similar locations.
More importantly, it's found the multi-variable explanation – not just "this segment is down" but the combination of factors that explains what's happening and how it compares across your operation.
The investigation that would take hours is done in seconds. And it's done the way your best executive would do it.
Beyond Answering Questions
When AI actually knows your business, it doesn't wait for you to ask.
Your best executives don't just answer questions – they investigate proactively. They look for patterns. They spot anomalies. They notice when something seems off, even if nobody asked.
Domain Intelligence works the same way. Because it has your executives' mental models encoded – and keeps refining them – it runs those investigation patterns across your entire operation, continuously.
Problems that would take weeks to surface in standard reports get caught in days. The executive who spent hours every morning reviewing dashboards now wakes up to completed investigations.
You stop searching for problems and start focusing on decisions.
Expertise That Finally Scales
Your most valuable asset is expertise, and it's trapped in people's heads. Your best operators know things about your business that aren't written down anywhere.
Traditional BI doesn't capture that – it just displays data. Generic AI doesn't capture it either – it just answers questions.
Domain Intelligence captures how your best people think, then applies it everywhere. The way your best person investigates one location is now how every location gets investigated, every day. And it keeps getting better as the system learns more about your business.
You're not replacing your experts. You're extending their reach across your entire operation – and building institutional knowledge that doesn't walk out the door.
The Point
There's a lot of generic AI getting bolted onto dashboards right now. Chatbots that can query data but don't understand what they're looking at.
What actually matters is simple: does the AI know your business?
Not just your data. Your business. The mental models that matter. The patterns worth investigating. The thresholds that separate noise from signal.
That's what Domain Intelligence captures – your executives' expertise, encoded, scaled, and continuously learning.
Because the point isn't AI that can talk to your data. The point is AI that thinks about your business the way your best people do.
Brad Peters is CEO of Scoop Analytics.
