Agentic AI 101: From answers to actions

October 12, 2026. 2-minute read.

What happens when AI starts taking action?

A chatbot answers your question.

An AI agent works toward a goal by choosing steps and using tools.

You give the agent a task, access to specific systems, and limits on its authority.

Consider a customer requesting an order update.

An agent might:

The difference is the ability to act across a workflow.

Why this matters

For your business, the opportunity is completing work faster.

The responsibility is deciding which actions you trust an agent to perform.

Two approaches help define human oversight:

Human-in-the-loop: a person reviews and approves specific actions before the agent proceeds. For example, approving a refund.
Human-on-the-loop: the agent operates within approved limits while a person monitors performance and intervenes when needed. For example, overseeing routine order updates and stopping execution when errors appear.

Human-on-the-loop requires visibility, clear escalation rules, and the authority to pause or stop the agent.

Before approving an agentic AI project, ask your team:

Start with a narrow workflow. Assign a business owner. Test with real scenarios, including failures.

Measure completed tasks, accuracy, cost, and exceptions requiring human intervention.

My takeawaygive AI agents clear goals, limited permissions, and accountable human oversight.

Which workflow in your business would benefit from an AI agent, and how would your team supervise the work?

Want to learn more?

A business perspective on redesigning workflows and turning agentic AI into measurable value. McKinsey

How human-agent teams change work, leadership, and organizational design.

A deeper introduction to how agents work, when to use them, and why transparency matters.

Mariano O'Kon speaks and advises on AI, cybersecurity, networking, infrastructure and the business impact of technology. Full bio