AI agents in everyday work: where should you start?

Start with a task your team recognises

Imagine a service coordinator opening an incoming request, finding the customer record, checking the relevant procedure and preparing a response. Today, those steps may involve several applications and repeated copying. An agent could help interpret the request, find supporting information and prepare the next action. This is an illustrative solution pattern, not a claim about a delivered client project.

The useful question is which part of that work needs interpretation, which part follows a rule, and who should authorise the result. Start there before selecting a model or buying another platform.

Understand the parts of an agent

A useful design has an instruction, approved knowledge, a set of permitted tools and an operating boundary. The instruction explains the task. Knowledge supplies context. Tools let the agent interact with systems. Boundaries define what it may answer or change. Microsoft Copilot Studio supports agents and workflows connected to business data and systems.

For example, a procurement assistant might find a purchasing policy and draft a requisition. Permission to draft should be separate from permission to place an order. A helpful answer and an authorised transaction have different consequences.

Choose a first use case with a clear boundary

Good candidates include an internal policy assistant, enquiry classification or a draft handover summary. Each has a recognisable user, a limited set of sources and an outcome someone can review. Avoid starting with a request to automate an entire department.

Write down the current steps, volume, common exceptions and time spent checking results. Agree a baseline before estimating benefits. Any time-saving figure should come from your own measured pilot.

Test the awkward requests

Use examples with missing details, outdated documents, conflicting sources and requests outside the agent’s remit. Include attempts to access another team’s restricted information. The expected behaviour may be to ask a question, refuse an action or hand work to a person.

Measure completion quality alongside effort: correct answers, unnecessary escalations, failed actions and review time. An agent that produces more checking work may need a smaller scope or better sources.

Your practical starting point

Pick one recurring task and collect representative examples. Identify its owner, approved sources, permitted actions and reviewer. Prototype the smallest useful version, then compare it with the existing process before widening its responsibility.