Modeling Logic Isn’t for Everyone

– And That’s the Point

One of the questions I get asked quite a lot —especially in meetings full of very smart, very ambitious people— is:

“Why can’t everyone on the business side just model decisions, cases, and processes using DMN, CMMN, and BPMN?”

Ah. If only it were that simple.

You see, that’s like asking, “Why can’t everyone write a symphony?”

Well… we all enjoy music. Some of us can play an instrument. Many of us hum along. But composing a full-blown symphony? That’s a métier. A craft. A skill honed over time.

And so is modeling logic. Decision models, case management models, process models—this isn’t just drawing fancy diagrams. It’s engineering. With a splash of storytelling.

Now, here’s the good news: just because not everyone should write these models doesn’t mean we can’t all read them. That’s the real beauty of standards like DMN, CMMN, and BPMN. They give us a shared language—a visual representation and a friendly-enough expression language for decision, case and process logic.

Let me put it another way.

Most of us speak English. We can read it. We can write emails. We can absolutely understand and enjoy a good novel.

But writing a great novel? That’s a job for a novelist.

And similarly, modeling logic isn’t about everyone grabbing a tool and building flowcharts in a frenzy. It’s about building high-quality, consistent, and understandable models—crafted by professionals.

But reviewed and understood by everyone. And that is the great difference with logic coded in a programming language. That cannot be easily read, reviewed or understood by most of us.

Now comes the second question—one I’ve been hearing more recently, thanks to our new digital overlord:

“Can’t AI write these models?”

And that’s a fair question. Because, yes, AI is getting pretty good.

It can write poems, generate marketing copy, even suggest process fragments.
So can it write models?

Well—maybe parts of them. AI can give you a draft. It can even help you debug a decision model or generate test cases. But it won’t understand your context.

AI might write a model.
But will it write your model?

Will it reflect your company’s mission, your tone of voice, your nuanced policies, your unwritten rules, and your obsession with legally bulletproof audit trails?

Probably not.

And let’s be honest: if it could, AI might as well take a seat on your management board. Perhaps next to Legal, with a laptop and a sense of irony.

But for now, that’s not happening. Because at its best, AI is an assistant. A co-pilot. Not the author. And certainly not the final approver of enterprise decision logic.

So where does that leave us?

It leaves us with a clear understanding that decision, case, and process modeling is a skill—a bridge between business insight and technical precision.
It’s a language, spoken fluently by professionals, but readable and reviewable by the entire organization.

It’s a shared canvas, where business strategy and vision becomes executable logic.

And if we want digital transformation to be more than a buzzword—if we want it to stick—we need to build those bridges intentionally.

Not by handing out modeling tools to everyone with a keyboard, but by building a culture of collaboration. A culture where modelers are empowered to craft.

And everyone else is empowered to understand, challenge, and improve.

Because just like writing a great novel—it takes a writer.

But it also takes readers who care about the story.