What is a copilot?
A copilot is an AI assistant embedded in a work application that drafts, summarizes, suggests, and answers questions while the person stays in control of the final result. The pattern first became widespread in software development, where a coding assistant suggests the next lines inside the editor, and the name has since spread to every kind of work application. Microsoft 365 Copilot is one example; it drafts emails, summarizes meetings, and builds slides from documents inside the Office applications. Many ERP, CRM, and ticketing vendors now ship a copilot of their own.
A copilot works from context. It reads the document, email thread, spreadsheet, or ticket the person has open, combines that with a request typed in plain language, and sends both to a large language model. Many copilots also retrieve related content from the company’s files and messages, so an answer about “the Q3 forecast” draws on the actual forecast file. The output appears as a suggestion the user accepts, edits, or discards.
Why a copilot matters
Copilots are the form in which most office workers first meet generative AI, because they arrive inside tools the company already pays for. They cut the time spent on first drafts, meeting notes, and finding the right file. They also change the governance picture overnight. A copilot that can read everything a user can read makes every over-permissioned file share visible in a way it never was before.
Kirk Tech Solutions typically treats a copilot rollout as a data governance project first, with a permissions review and a data classification pass completed before licenses are assigned.
Copilot compared with an AI agent
A copilot waits for a request and returns a suggestion inside one application. An AI agent pursues a goal across several steps and systems, calling tools and acting with limited supervision. The line blurs as vendors add actions to copilots, such as sending the email it drafted or updating the record it summarized. Once a copilot can change a system of record, it needs the same approval workflow and audit log an agent does.
What to watch for
- Audit file and mailbox permissions before turning a copilot on, because it will surface whatever users were already allowed to see but could never find.
- Ask where prompts and retrieved content are processed and whether they are used to train the vendor’s models.
- Check which actions the copilot can take on its own and whether each one is logged with the user who approved it.
- Expect uneven results across tasks; summarizing a meeting is reliable, while reasoning over a large spreadsheet often is not.