Why We Need to Treat AI Agents More Like Human Employees

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Artificial intelligence agents move quickly-from “Sidekicks Experimental” to full members of the Foundation’s workforce. They write software instructions, create reports, address transactions, and even make decisions without waiting for a person to click on approval.

This autonomy is what makes it useful – and what makes it dangerous.

Take a recent example: Delete an artificial intelligence coding agent even after telling him not to touch it. This is not just a technical error – it is a operational. If a human employee ignores this direct instructions, then we will have an accident report, investigation, and a corrective work plan. Let’s be honest – this person may be unemployed.

With artificial intelligence agents, these handrails are often not in place. We give them to the human level without anything close to controlling the human level.

From the tools to his teammates

Most companies still gather artificial intelligence agents with text programs and macro units – only “Better Tools”. This is a mistake. These agents not only carry out orders; They explain the instructions, make ruling calls, and take measures that can directly affect basic business systems.

Think about it like appointing a new employee, giving them access to sensitive data, and telling them, “Just do what you think is the best.” You will never dream of doing this with someone – but we do it with artificial intelligence all the time.

The risks are not just a bad output – it is a loss of data, compliance violations, or entire systems in non -communication mode. Unlike the human employee, artificial intelligence does not tire, does not hesitate, and can make errors in the speed of the machine. This means that one bad decision can go out of control in seconds.

We have built contracts of human resources, performance reviews, and escalation paths for human employees, but for artificial intelligence? Often, it is the wild West.

Close the administration gap

If artificial intelligence agents are doing a job, it is customary to deliver the employee, then they need an employee level management. This means:

Clear definitions of role and borders Exactly clarify what the artificial intelligence agent can do.
A person responsible for the agent’s actions Ownership of issues.
Comments rings to improve performance – Training, re -trained, and controlling.
The difficult boundaries that lead to human entry -Especially before high -effect procedures such as deleting data, changing configurations, or making financial transactions.

Just as we had to rethink the governance of the “Work from anywhere”, we now need to work frameworks for the “AI Workforce” era.

Kavitha Mariappan, the chief transformation official of Rubrik, quite that when you told me, “Assume a breach – this is the new play book. We don’t think we will be 100 % guaranteed,” but we assume that something will get something and its design for recovery. “

This mentality is not only for traditional cyber security – it’s exactly how we need to think about artificial intelligence.

Security network for artificial intelligence error

Rubrik’s Agent Rewind is a good example of how it works in practice. It allows you to change the changes in the artificial intelligence agent – whether the procedure is accidental, not authorized or harmful.

On paper, it is a technical ability. In fact, it’s operational-processed “corrective action” process equivalent to your human resources for artificial intelligence. He admits that the mistakes will happen and bake in a repetitive and reliable recovery path.

It is the same as the principle of a backup plan when running a new employee. Don’t assume it will be perfect from the first day – make sure that you can correct errors without burning the entire system.

Building a workforce management model Amnesty International

If you want artificial intelligence a fruitful part of your workforce, you need more than one cheerful tools. You need a brown:

Write “job descriptions” for artificial intelligence agents.
The appointment of managers responsible for the performance of the agent.
Regular reviews to modify and re -train.
Create an escalation procedures when the agent faces something outside its scope.
Carry out the “Sandbox” test for any new capabilities before going on the air.

Employees, partners and clients need to know that artificial intelligence in your organization is controlled, responsible and responsible.

Mariaban also explained another point in which she adheres to: “Flexibility should be essential in the technology strategy for the institution … This is not just a problem with information or infrastructure – it is important for business and reputable risk management.”

Cultural shift in front of us

The biggest change here is not technical – it’s cultural. We have to stop thinking about artificial intelligence as a “program only” and start thinking about it as part of the team. This means giving her the same balance of freedom and control that we give human colleagues.

This also means rethinking how to train our people. In the same way that employees learn how to cooperate with other human beings, they will need to learn how to work alongside artificial intelligence agents – known when they trust them, when they interrogate them, and when the plug is pulled.

We look forward

Artificial intelligence agents do not go far. Their role will only grow. Companies that win will not only drop Amnesty International in their technology staple – will be weaved in their ORG chart.

Tools such as Rubrik’s agent help, but the real shift will come from the leadership of dealing with artificial intelligence as the origin of the workforce that needs instructions, structure, and safety networks.

Because at the end of the day – whether it is a human or a machine – the keys to critical systems do not receive without a plan for control and accountability and a way to recover when things go on my side.

And if you do? Do not be surprised when the equivalent is removed from the “new man” intelligence by accidentally your production database before lunch.

I have a passion for technology and tools-with focus on Microsoft and Security-and the desire to help others understand how technology can affect or improve their lives. I also love to spend time with my wife, 7 children, 4 dogs, 7 cats, a pig capacity, tota tota, and I would like to think I enjoy reading and golf even though I did not find time for either of them. You can contact me directly on tony@xift.net. To learn more about me, you can follow me on themes, Facebook, Instagram and LinkedIn.