A five-step guide to staying in control when AI gets it wrong
If AI makes a mistake, such as giving customers the wrong information, booking appointments incorrectly or creating avoidable errors, knowing how to respond quickly can protect customer trust, reduce disruption and keep your business moving.
At a glance
What can go wrong
AI tools can make mistakes and produce incorrect output if they're using outdated information, have unclear instructions or are performing tasks they haven't been set up to handle.
What to do first
Pause the affected function or add human approval to contain the problem, investigate what happened, contact anyone affected, fix the cause and record what you’ve changed.
Why it matters
A simple response plan helps you reduce risk, protect trust and keep getting value from AI.
How to stay in control – the five-step guide
AI tools can help your business move faster, support customers more efficiently and reduce repetitive admin. But they still need accurate information, clear instructions and the right human oversight.
If an AI tool gives a customer the wrong information, books the wrong appointment or produces other AI errors, the priority is to stay in control. Think of your response in three parts: contain the problem, investigate what happened, then recover safely. Follow these five steps in order to contain the issue, put it right and reduce the chance of it happening again.
Step 1: Pause the affected function to contain the problem
Pause the part of the AI tool causing the issue or add human approval while you investigate. If you’re not sure where the problem is, pause the tool more widely until you understand what happened. The priority is to stop the mistake spreading before you investigate the cause. Know how to switch the tool off, pause it or limit what it can do before you start using it.
Example
If your AI receptionist shares last year’s opening hours, switch it off until the information has been checked and updated.
Step 2: Check what went wrong and who was affected
Check what the tool did, who was affected and how far the mistake went. Review any transcripts, prompts, source information and automated actions. This helps you understand whether the AI mistake was caused by outdated information, unclear instructions, a missed human check or a task the tool should not have handled.
Example
If an AI meeting summary says a client agreed to a proposal when they only said they would think about it, check the transcript and whether a person reviewed the summary before it was sent.
Step 3: Contact customers to make them aware
If you’re using an AI tool, you should always ensure customers know you are doing this. Then, if the AI makes a mistake, it won’t come as a huge shock. And, of course, you should always contact any affected customers as soon as possible to correct the error and put things right.
Example
Do this if you’re using AI to transcribe a meeting and it has got some important details wrong. For instance, if a follow-up email confirmed Tuesday for a meeting that was agreed for Thursday, contact the client straight away to clarify the date and share the correct details.
Step 4: Fix the cause before switching it back on
Fix the issue before you switch the tool back on. Check whether the source information is accurate, the prompt is clear, the tool is being asked to do the right job and any human approval steps are working as planned. Test the corrected function with realistic examples, check the same mistake no longer happens, then reintroduce it gradually with a person checking the output.
If you can’t find the cause, contact your vendor’s support team. Keep a named person responsible for regular checks, so mistakes are easier to spot and fix early.
Example
If the AI double-books appointments, change the process so bookings are treated as requests and confirmed by a person before they go into the diary.
Step 5: Record what happened so your team can learn
Record what happened in clear, simple language. Include what went wrong, who was affected, what you changed and the date. Share it with your team so everyone can learn from the incident and respond consistently if it happens again.
Example
Create a short, shared note for AI incidents. Over time, this becomes a useful record of what happened, what changed and what your team should check next.
Stay in control, even when AI gets it wrong
AI doesn't need to be perfect to be valuable. What matters is having the right checks in place and knowing how to respond when something goes wrong. With a simple process and the right level of oversight, you can use AI confidently while staying in control of the outcomes.
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