Where AI Agents Help, and Where They Should Stop
A practical framework for agentic AI: which tasks suit AI agents, how to set levels of autonomy, and why people should approve consequential actions.
Technology
Agentic AI and how much autonomy to allow
AI agents plan steps, call tools and act. The useful question is never whether an agent can do something, but how much it should be allowed to do alone, and who answers for the result.
Quick answer
Quick answer
How much autonomy should an AI agent be given?
Autonomy should be granted in levels and earned with evidence. An agent can start by gathering information, then suggesting an action, then preparing it in full for approval. Acting alone is reserved for low risk, reversible tasks inside monitored limits. Anything that moves money, changes customer records, communicates externally or affects someone's health needs a named person to approve it.
A ladder of autonomy
Inform
The agent gathers and summarises information. A person decides everything.
Suggest
The agent proposes an action with its reasoning. A person chooses.
Prepare
The agent drafts the action in full. A person approves before anything happens.
Act and report
The agent acts on low risk, reversible tasks and reports every action for review.
Act within limits
The agent acts alone inside tight, monitored boundaries, with automatic escalation.
A task moves up the ladder when there is evidence that it behaves at the level below: a log of decisions, a rate of correction that is low and falling, and a person who can say what the agent did last week.
What this looks like in practice
Rohit's agentic work runs from small internal assistants to platform scale implementation, including Workologix, an agentic AI and automation platform, for one of the leading logistics companies in the United States. The pattern repeats at every size. The model is rarely the hard part. The hard parts are the boundaries, the logs, the escalation path and the review screen that makes checking an agent's work faster than doing the work by hand.
Failures are designed for rather than hoped against. Every agent has a way to be switched off, a record of what it changed, and a defined owner. If nobody can answer who is accountable for an agent's action, the agent is not ready to take it.
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Questions
Questions about agentic ai and autonomy
What is an AI agent?
An AI agent is a system that plans a sequence of steps, calls tools or other software to carry them out, and works towards a goal rather than answering a single question. The planning and the tool use are what separate an agent from a chat assistant.
Where should agents not be used?
Anywhere a wrong action is expensive and hard to reverse without a person in the loop: payments, contracts, customer records, public communication and anything that affects someone's health or safety.
Does accountability transfer to the software?
No. Responsibility stays with the organisation and the named person who approved the automation. That is why logs, limits and a clear owner matter more than the model.
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