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# How to Know Whether AI Is Making Correct Decisions in Operations?
- URL: https://blog.jestor.com/correct-ai-decisions-in-operations-2026/
- Published: 2026-09-04T20:07:22.000Z
- Updated: 2026-09-04T20:07:22.000Z
- Author: Bruno Bannach

Knowing whether correct AI decisions in operations are actually happening depends on tracking three things: the rate of exceptions that need human review, the consistency of responses in similar cases, and feedback from whoever uses the result day to day. No AI decision should run without some kind of check.

This is a legitimate concern for anyone leading operations: letting an agent decide on its own seems risky, especially when the decision affects a customer or money. The question isn't whether AI makes mistakes, it's how to catch the error in time.

The good news is that you can structure this tracking without turning it into a complex project. What matters is defining, from the start, what counts as a correct decision for that specific process.

## Signs something might be wrong

- The volume of exceptions or manual corrections growing over time
- Different answers for practically identical situations
- Complaints from customers or the team about the automation's results
- Decisions that fall outside the standard with no clear justification

## How to track decision quality

- Define simple metrics from the start, like accuracy rate and manual review rate
- Keep a human reviewing a sample of decisions, even with the process automated
- Record the reasoning behind each decision, not just the final result
- Adjust the agent's rules whenever an error pattern repeats

## What to do when AI gets it wrong

- Isolate the case and figure out whether it was a rule failure or a one-off exception
- Fix the rule before letting the agent keep making the same decision
- Communicate the change to the team, to maintain confidence in the process
- Document the adjustment, to avoid repeating the same error in another flow

## How Jestor helps track AI decisions

- Chat with Data on **[Jestor](https://www.jestor.com/?ref=blog.jestor.com)** lets you query decision history in natural language
- Jestor's AI Record Editing keeps track of what was changed and why
- Jestor's AI Agents can be configured to escalate cases outside the standard to a human
- Companies like Enforce and Asaas use **Jestor** to closely track automated processes

## Frequently asked questions

**How do I know if AI is making correct decisions in operations every day?** By tracking the exception rate and periodically reviewing a sample of decisions. See more at [jestor.com](https://www.jestor.com/?ref=blog.jestor.com).

**Do I need to review every decision made by an AI agent?** Not every one, but keeping a sample under constant review is recommended.

**What should I do when an AI agent makes a wrong decision?** Fix the rule behind the decision and communicate the change to the responsible team.

Ensuring correct AI decisions in operations is an ongoing process, not a one-time setup you can forget about.

## Get to know Jestor

With Jestor, you can automate workflows, connect departments, and build internal systems your way, all without code and with AI support. Get to know Jestor at [jestor.com](https://www.jestor.com/?ref=blog.jestor.com) and discover how to take your company's management to a new level of efficiency and integration.