By Ugochukwu Lean Asiegbu, PMP®, Founder, White Key Advisory
Every AI system can make mistakes. Businesses are better prepared when they decide, before launch, how those mistakes will be caught and who is responsible for acting on them.
Plan for errors before launch
Errors and interruptions happen in software, spreadsheets and manual processes. AI systems also need clear processes for detecting and correcting problems.
An AI assistant may misread an enquiry, draft a reply with the wrong date or route a request to the wrong person. A workflow may stop when a connected service changes. Planning for these possibilities means putting oversight, responsibilities and a response plan in place from the start.
Three questions to answer before you build
Before an AI system goes live in your business, you should be able to answer three questions clearly.
1. How will the AI system be monitored?
Decide what “working correctly” looks like and how you will know when it is not.
That might mean reviewing outputs regularly, tracking how often staff correct the system or setting an alert when a workflow stops running. The level and timing of review should reflect the consequences of a mistake. High-impact outputs may need approval before any action is taken.
Monitoring also supports measurement. Comparing performance against the baseline agreed before implementation helps you assess whether the system is improving response times, accuracy or administrative workload.
2. Who will monitor the AI system?
“The team” is not a sufficient answer.
Name a person or role responsible for oversight, and make sure they have the time, access and authority to act. In a hotel, that might be the front-office manager. In an estate agency, it might be the principal or an operations lead.
Agree who covers that responsibility when the usual reviewer is unavailable.
3. When something goes wrong, who can pause it?
Someone must be able to pause the affected workflow promptly, through an agreed procedure.
Decide in advance what triggers a pause, how it is done and what the manual fallback will be while the issue is investigated, so clients are still served while the system is offline.
Before restarting, check that the problem has been addressed, the workflow has been tested and any affected enquiries or tasks have been followed up.
Human accountability is the safeguard
Clear human accountability helps businesses use AI responsibly. In practice, that means:
- A human review step before sensitive outputs reach a client, such as a quote, booking confirmation or commitment.
- A named owner for each system, recorded and known to the team.
- A simple record of what the system did, what was corrected and why.
- A tested way to pause the workflow, with a manual process to fall back on.
These safeguards may add review steps, but they help businesses catch mistakes, protect service quality and use AI with greater confidence.
How White Key Advisory approaches this
At White Key Advisory, oversight forms part of the initial assessment and solution design.
Our method—Identify, Design, Automate, Measure—includes defining who reviews outputs, how performance will be assessed against an agreed baseline and how a workflow should be paused if something goes wrong.
The aim is practical AI that supports your operations, with people accountable for important decisions.
Can you answer these three questions for your business? If not, we can work through them together.