AI copilot

How it works

A copilot lives inside a tool: the inbox, the CRM, the help desk, the code editor, a Slack channel. It reads what is on the screen or in the record, plus whatever company knowledge it is connected to, and offers a draft. The person accepts it, edits it or ignores it. That last step is the difference from an AI agent, which acts on its own.

There are 2 ways to get one. Buy the copilot your vendor ships, such as Microsoft 365 Copilot (opens in a new tab) or GitHub Copilot (opens in a new tab), or build a narrow one on a model API that knows your documents and your process. Bought copilots are broad and general. Built ones do one job with your data, and you own them.

How businesses use it

The best copilot jobs are frequent and easy to check:

• Drafting help desk replies from past tickets and the policy library
• Summarizing a sales call into CRM fields and a follow-up email
• Answering staff questions about HR or IT policy inside Slack or Microsoft Teams
• Turning meeting notes into a project update in the house format

Most of these need a RAG knowledge system underneath, so answers come from your documents and cite them. Teams also need an hour on what to trust and what to check. Our AI workshops cover that with your own examples.

Where it goes wrong

Copilot errors are easy to miss. People stop reading drafts closely after the first 50 good ones, so the 51st wrong answer goes out under their name. Track how often drafts are accepted without edits and spot-check a sample every week.

The other common failure is license sprawl: seats bought for a whole department when 6 people use them daily. Pilot with a small group, measure usage for a month, then expand. And if the job needs the assistant to take actions across systems, you need an agent with approval steps and guardrails, which is a different build with a different risk profile.