Yes, you can fail at automating: 5 common mistakes in RPA projects
By Kaique Jesus do Nascimento — Head of AI Solutions
Automation is one of the strongest promises of digital transformation. But in practice, what should reduce effort often turns into a headache when a few basic mistakes go unnoticed.
In RPA (Robotic Process Automation) projects, I’ve observed recurring issues that compromise not only the bots’ performance, but also the credibility of automation within organizations.
Here are the five most common mistakes:
1. Poorly defined processes
If the process isn’t clear for humans, it won’t be clear for robots either. Automating chaos only delivers chaos faster.
2. Lack of structured testing
Many bots go live without being tested under different scenarios, increasing the risk of failures in unmapped cases. And when something goes wrong, the source of the problem isn’t always easy to identify.
3. Missing governance
Without basic control structures (versioning, ownership, monitoring) RPA becomes a black box. When errors occur, no one knows where to start fixing them.
4. Misalignment between IT and business
Some bots are built with a purely technical or purely operational focus, without considering the real impact on the company’s broader workflow. The result? Automation that doesn’t serve the strategy it was meant to support.
5. Neglected maintenance
Automation is not a “set and forget” initiative. Changes in systems, fields, or business rules can break bots overnight. Without a clear maintenance plan, losses are only a matter of time.
These mistakes create rework, internal resistance, and long-term doubt about the value of automation itself.
If your company is thinking about automating, start by getting it right.