What an AI agent can actually take over

Ask five people what an AI agent can do and you get five different answers, most of them wrong in one direction or the other. Here is what we have actually seen work, in production, for Egyptian businesses running real workflows.

What agents handle well

• Reading an inbox and sorting it into categories a person defined.
• Drafting a reply from a template and the message it answers.
• Pulling structured fields out of an unstructured document — an invoice, a booking form, a contract.
• Writing a first draft of a report from data that already exists in a system.

Each of these has one thing in common: the rules for a correct answer already exist somewhere, even if nobody wrote them down before the agent arrived.

What still needs a person

• Any decision whose cost of being wrong outweighs the cost of asking a person first.
• Judgment calls where the right answer depends on context the agent was never given.
• The first hundred cases of anything new. An agent needs examples before it needs autonomy.

An agent that is right nine times out of ten is not nine-tenths of an employee. It is a tool that needs a person watching the tenth case.

A pattern that works

The agents we build follow the same shape every time: the agent handles the routine case end to end, and hands off anything it is not confident about.

inbox message arrives
  -> agent classifies it
  -> routine case: agent drafts the reply, sends it
  -> anything else: agent flags it, a person decides

That handoff line is the whole design problem. Draw it in the wrong place and the agent either does too little to matter or too much to trust.

Figuring out where that line sits for your own workflow is the first thing we do together, before any code is written. See how we approach it.