You wouldn't hand a new hire a task list on their first day, then disappear for three months. Most businesses do exactly that with their AI.
That is really what implementing AI agents in a business comes down to. McKinsey found that 88% of organisations now use AI in at least one part of the business, up from 78% the year before. Only 6% count as AI high performers, seeing real value from it. The gap between those numbers has nothing to do with the technology. It is about what happens after the tool gets switched on.
A new employee gets a job title, a manager, a first week of training, and someone checking their early work. An AI tool usually gets none of that. It gets access to a system and a vague hope that it will help.
That is not onboarding. That is installing software and walking away.
A new staff member handed ten half-explained responsibilities and no manager will struggle, however capable they are. An AI worker is no different.
The businesses that get this right give their AI worker one named job. Chasing overdue invoices. Following up dormant leads. Drafting the first version of a report. One job done properly beats five jobs done badly.
Every new hire gets a manager. Every AI worker needs one too.
Picture a business that sets up an AI worker to answer inbound enquiries. In week one, someone reads every reply it sends, checks the tone, and fixes the mistakes. By week four, the AI worker handles most enquiries well on its own, and the manager only steps in for the tricky ones. That is what proper onboarding looks like. It is not a switch you flip once. It is a relationship you build over weeks.
Skip that step and the tool that worked brilliantly in the demo quietly stops being anyone's job to manage.
Start with a job description, just like you would for a person. What exactly is this AI worker responsible for, and what is out of scope? Then name an owner inside the business, someone whose job it is to check the work every week, not just in the first month.
Set a simple way to measure whether the job is being done well. Response times, accuracy, how often a human has to step in and fix something. Then let the oversight ease off as trust builds, the same way it would with a new employee who is proving themselves.
Most AI tools work well enough, straight out of the box. What is missing in most businesses is the habit of managing them properly, the same way they already manage people. That is the difference between an AI worker that pays for itself and one that quietly gets ignored six months in (read more on what an AI worker actually is).
If an AI worker has been running in your business for a few months and nobody could tell you who owns it, or how you would know if it was doing a good job, that is worth a proper look here.
Ready to see what AI transformation looks like for your business?
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