How a copilot differs from a chatbot and an agent
A chatbot waits to be asked and starts from nothing. A copilot already knows the record on screen, the document open, the ticket being worked, and offers something useful without being briefed. An agent goes one step further and acts on its own. A copilot proposes; a person accepts.
What makes a copilot work
- Context, read from the application rather than typed in by the user.
- A suggestion offered where the work happens, not in a panel to the side.
- A review step, so accepting is deliberate and reversible.
- Measurement of acceptance, because a suggestion nobody takes is a failure regardless of how often it appeared.
Why copilots get ignored
Three reasons, repeatedly. Suggestions arrive without enough context to be right. Accepting one costs more effort than doing the task by hand. Or the user cannot see what changed afterwards, so they stop trusting it. Each is a design problem rather than a model problem, which is why a better model rarely fixes an ignored copilot.
How is a copilot measured?
On acceptance rate, not on engagement. Engagement counts how often it was shown; acceptance counts how often it was right enough to use. Those numbers diverge quickly, and only one of them tells you whether the feature is working.
Related
- AI copilot development: built into your interface rather than beside it.
- What is an AI agent?: the version that acts rather than proposes.