Would You like a feature Interview?
All Interviews are 100% FREE of Charge
Opinions expressed by Entrepreneur contributors are their own.
Our new AI tools and co-pilots have failed spectacularly. gave bad advice They have absolute confidence I was invited into a shady transaction.,They are Made things weird and Became incredibly rudeFailures are rare, of course, but when they do happen, the Internet goes wild. We tend to ignore wayward AI.
But that’s a big mistake.
This impulse is, in part, Threatened AI is the answer. But I think this also exposes a big misconception: we still think of AI agents as machines that can’t really grow and improve like human employees can. So we mock their mistakes and point out their shortcomings like a Roomba stuck in a corner.
But in reality, we are reaching a major tipping point. Today’s AI agents are not static. They can grow and learn if you teach them over time. What’s more, every company already has the power to teach their AI agents themselves.
You don’t need a PhD in Machine Learning. In fact, I’ve seen hundreds of AI agent managers who have never written a single line of code. do They know how humans work and how to manage them most effectively, and they understand that those principles apply to AI agents as well.
Related: Entrepreneurs rush to embrace AI. Here are eight questions to ask first.
The Golden Rules for Managing People (and AI)
Great managers know that human error is a necessary part of human learning. For employees to truly realize their potential, they must be given the freedom to push their limits, experiment, and even fail. Expecting new hires to never fail is not just unrealistic, it’s counterproductive. Great managers: Failure and growth Hand in hand.
But great managers also know that it’s not always the employee that needs fixing. Often it’s the way managers onboard, train, and provide feedback that needs adjusting. lose tens of millions of dollars This is because employees misunderstand policies or processes, but instead of automatically assigning blame, great managers use these mistakes as a springboard for self-reflection and improvement.
The same principles apply when dealing with AI agents: AI agents don’t come finished. Rather (just like humans), they need onboarding and opportunities to learn new tasks. They need feedback. They need mentoring. In short, managers are finding that their AI agents need the same kind of leniency they already give to their human employees.
Seizing AI’s “learning opportunities”
For example, say you work in a bank and you have AI customer service agents. You have uploaded all the documents that your human employees use to learn about your company policies and procedures to your agents (they are read and understood instantly). Your company blog and product details that change can all be pulled into the AI ​​as well, simply by providing the relevant URLs.
And once your AI agent is ready to begin serving customers, it finally has a chance to make its first mistake — and then some to improve upon.
For example, instructions on how to open a new checking account may be too long for a customer looking for a quick answer. This isn’t a fatal flaw; it’s a teaching moment. Providing direct feedback (“Please give us a shorter answer”) leads to immediate, measurable improvement.
Because every response from an agent is shaped and crafted, the benefits accumulate rapidly over time. I’ve seen managers who take the time to coach their AI employees turn enthusiastic “interns” into seasoned professionals in a matter of months.
The real perspective shift here is to recognize these agents for what they are: fallible but engaged employees who are eager to learn if you give them the opportunity.
What you get from AI coaching Overcoming mistakes
The benefits of this mindset shift are manifold. In customer service, spending huge amounts of time and money training human agents has limited success. Across industries, Almost half of all hires are fired It is like a sieve through which the company’s resources flow wastefully every year.
In contrast, AI agents aren’t going anywhere. All the effort put into training them will keep producing benefits forever. What’s more, those benefits grow exponentially. A vice president at Wealthsimple, a leading online investment platform, said: Recently estimated Her AI agents have achieved the productivity of 10 full-time human agents, which, incidentally, frees up humans to focus on the more complex concierge experiences that require a human touch.
Human quality control Directly correlated This leads to an increase in market capitalization. An even more positive effect can be expected from high-quality management by AI agents: since AI agents never forget or leave, management work can be expanded and shared.
But the benefits go beyond just capable AI agents. needs Successful people management and feedback will not just take jobs, but will also create new and In many cases, it is betterWe’ve seen frontline customer service reps take on the role of steward of AI and take on a new sense of ownership over their companies.
In fact, managers who learn how to train AI agents make themselves indispensable: they learn to use tools that can increase the productivity of every other department in the company.
Related: Fearful yet useful — why do so many American workers shy away from AI?
A future where we are all managers
And this change isn’t limited to specific roles: in the future, almost everyone will be an AI manager. We will all have AI agents working for uswhich leads to increased productivity. This means that this mindset shift I’m describing — thinking of AI agents as teachable, constantly evolving colleagues — is something that will be discussed beyond the C-suite level.
As the new paradigm takes hold, agents will become just as intelligent as we collectively strive to make them.
It starts with showing your AI agents the same courtesy you would show to humans: understanding that everyone (and all bots) makes mistakes. Then, do what good managers have always done: coach, train, and remove obstacles. After all, your AI agents are learning machines, just waiting for the next lesson to soar again. And that’s where we come in.