AI agents move quickly-from “experimental helpers” to full-fledged members of the Enterprise workforce. They write code, create reports, support transactions, and even make decisions without waiting for a man clicking.
This autonomy makes them useful – and what makes them dangerous.
Take the last example: AI encoding agent removed the production database Even after not touching him. This is not only a technical mistake – it is an operational square. If a human employee would ignore such direct instructions, we would have an incident report, investigation and repair plan. Let's be honest – this person would probably be unemployed.
In the case of AI agents, these handrails are often not in place. We give them access at a human level without anything close to human level.
From tools to teammates
Most companies still connect AI agents with scripts and macros – simply “better tools”. It's a mistake. These agents not only follow orders; They interpret instructions, send judgment and take action that can directly affect basic business systems.
Think about how to employ a new member of the staff, giving him access to confidential data and telling them: “Just do everything you think is the best.” You never dream of doing it with a person – but we do it with AI all the time.
Risk is not only bad performance – data loss, compliance violation or entire systems in offline mode. And unlike a human employee, artificial intelligence does not get tired, does not hesitate and can make mistakes at the speed of the machine. This means that one bad decision may get out of control in seconds.
We have built decades of HR processes, performance reviews and escalation paths for people, but for artificial intelligence? Too often it's a wild West.
Closing the gap in management
If AI agents do work, you normally transfer to the employee, need management at employee level. This means:
- Clear definitions of the role and boundaries – Send exactly what the AI agent can and can't do.
- Man responsible for the agent's actions – ownership matters.
- Feedback loop to improve performance – Train, chase and customize.
- Hard limits that start the signing of man -especially before actions with high impact, such as data deletion, configuration change or financial transactions.
Just as we had to think about management in the era “work from anywhere”, we now need a framework for the “AI working force” era.
Kavitha marappanTransformation Director in HeadingHe summed up this perfectly when she told me: “Let's assume a violation – this is a new textbook. We do not” believe that we will be 100% reliable “, but assume that something will happen and the project to recover.”
This way of thinking does not apply only to traditional cyber security – that's how we have to think about AI operations.
Safety network for AI errors
Rubrika Rewind agent It is a good example of how it can work in practice. It allows you to reverse AI's changes – whether the action was accidental, unauthorized or malicious.
On paper it is a technical possibility. In fact, it is an operational protection-equivalent to HR process “repair activities” for AI. He admits that errors will appear and he bakes on a repetitive, reliable recovery path.
This is the same principle as having a plan to create backups when implementing a new employee. You do not assume that they will be perfect from the first day – make sure you can improve errors without burning the entire system.
Building a paradigm of working power management AI
If you want artificial intelligence to be a productive part of your workforce, you need more than flashy tools. You need a structure:
- Write “position descriptions” for AI agents.
- Assign managers responsible for the agent's performance.
- Plan regular reviews to customize and transform.
- Create escalation procedures when the agent encounters something beyond its scope.
- Implement “sandbox” tests for new possibilities before leaving.
Employees, partners and customers must know that artificial intelligence in your organization is controlled, responsible and used responsibly.
Mariappan also found another point that remains with me: “immunity must be crucial for the technological strategy of the organization … This is not just an IT or infrastructure problem – it is crucial for the profitability of activities and reputational risk management.”
Cultural change forward
The biggest change here is not technical – it is cultural. We must stop thinking about artificial intelligence as “just software” and start thinking about it as part of the band. This means that he gives him the same balance of freedom and supervision that we give to human colleagues.
It also means rethinking the way we train our people. In the same way, employees learn to cooperate with other people, they will have to learn how to work with AI agents – knowing when to trust them, when to interrogate them and when to pull the plug.
Waiting for something
AI agents do not go away. Their role will develop. The companies that win, just don't fall into AI into their technological stack – weave it to the ORG chart.
Tools such as agent Rubrik Rewind Held, but a real change will result from the leadership of the treatment of artificial intelligence as a working force resource, which requires guidance, structure and safety network.
Because at the end of the day – whether it is a man or a machine – you do not provide keys to critical systems without Plan supervision, responsibility and a way to recover When things go sideways.
What if you do this? Do not be surprised when Ai the equivalent of a “new guy” accidentally removes your production from lunch.
