You can’t automate what you don’t understand

I hope this isn’t news to you – but it might explain why so many companies struggle to bring data, processes, and AI together in a meaningful way.

Why this topic?
Last week I had the pleasure of attending the Process Intelligence Days hosted by Celonis in Munich.
Yes, there was plenty of sales and marketing. But more importantly, there were eye-opening customer stories about using process mining not just as a reporting tool – but as a daily driver for automation, data fluency, and ultimately, AI.

Here’s what struck me:
For all the AI we already use in our personal lives, AI in business is still in its infancy.

Why?
Because most organizations forget a hard truth:
If your processes are messy and your data is poor, no AI in the world will save you.

Just like with every wave of technological innovation, you need to clean up your foundation first.
That means: understanding your processes, closing data gaps, and building clarity before you automate anything.

If you’ve recently tried launching an AI initiative and felt underwhelmed by the results – you're not alone.
The most successful cases I heard last week all had one thing in common:
They started with transparency and discipline before reaching for AI.

Process mining might not be flashy – but it’s your shortcut to actual business impact.