01From assistant to colleague
A chat assistant waits for a prompt and returns text. An AI employee is set up around an outcome: preparing the weekly sales report, drafting customer follow-ups, or keeping product data clean. It knows which systems to read from and which to write to.
The term is mostly marketing shorthand, but it points at something real: work that is delegated, not just assisted. The useful question is not "is it an employee?" but "which job does it own, and who checks the output?"
02What makes it work in practice
Three things separate a working AI employee from a demo: connections to real systems (CRM, ERP, shop, inbox), a clear scope, and a human approval step. Without approval, mistakes reach customers. Without scope, the agent tries everything and does nothing well.
This is why teams increasingly run agents where they already talk to each other. Switch builds custom agents inside Teams and Slack that your team can tag by name, with a person approving every output.
03General-purpose vs custom
Tools like ChatGPT or Claude cover the basics: writing, summarising, brainstorming. Workflows with real business impact usually need a custom agent that understands your data, formats and rules. Many companies end up with both layers.