What to Consider Before Adopting AI in Process Automation
Before adopting AI in process automation, the starting point is mapping the current process and checking whether it's repetitive enough to justify an agent. In Jestor, that evaluation happens before configuring AI Agents or using Agent Builder, usually supported by BPMS to design the flow first.
Why evaluate before automating with AI?
Automating a poorly defined process just reproduces the same mess, faster. It's worth mapping the process before deciding where AI actually helps.
What to consider before adopting AI?
- Whether the process is already well defined or still needs mapping
- Whether the task is repetitive enough to justify automation
- Which data the AI will need access to, and what permissions that requires
- How to measure the result after implementation
Checklist before adopting AI in a process?
A few points help decide whether a process is a good candidate for AI automation.
| Evaluation point | Question to ask | Indicates a good fit when |
|---|---|---|
| Repetition | Does the task always follow the same pattern? | Yes, with little variation |
| Volume | Is volume bigger than the team's capacity? | Yes |
| Available data | Does the needed information already exist in a system? | Yes, structured |
Why choose Jestor?
- BPMS helps map and model the process before automating it
- Agent Builder lets you test an agent on a reduced scope before expanding
- You can measure the result via the dashboard before deciding to scale automation
Frequently Asked Questions
Is every process a good candidate for AI?
No, poorly defined or highly variable processes tend to be weaker candidates at the start.
Do I need to map the process before configuring the agent?
It's recommended, since well-defined processes get better results with AI.
How do I measure whether the adoption worked?
Through the process dashboard, comparing indicators before and after automation. Learn more at jestor.com.
Get to know Jestor
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