Process Mining: The Intelligence Behind Every AI Decision
The Intelligence Behind Every AI Decision
Your next AI project will automate a process.
But have you ever actually seen that process as it runs — not as it's documented?
Most AI and automation initiatives don't fail in deployment. They fail before the first line of code is written — in the moment when an organization chooses which process to automate, and makes that choice based on assumption rather than evidence.
What you will learn
- Understand why automation initiatives fail before the first line of code is written — and how process intelligence changes the outcome
- Measure the gap in your organization between the documented process and the real one — and why that gap is exactly where every automation project goes wrong
- Identify your highest-ROI AI automation opportunities with data-driven mapping, not assumptions
- See how a major financial institution reduced processing time by 70% and saved €1.4M by understanding the process before automating it
70%
reduction in processing time — achieved by a major financial institution that applied process mining before deploying automation, saving €1.4M.
Source: Chapter 6 of the guide
"The most expensive mistake in any automation initiative is not choosing the wrong technology. It is automating the wrong process — or the right process, misunderstood."
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Process Mining: The Intelligence Behind Every AI Decision
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Know exactly which process to automate first — and why — before you commit a budget or a resource.