"AI assistant", "AI agent", "AI coworker" — marketing teams use all three terms to describe roughly the same product behavior: AI bolted onto a tool. But they point at meaningfully different things, and picking the wrong mental model leads to misplaced expectations and wasted subscriptions.
An AI coworker is a model that has been given a seat in your shared workspace. It works real tasks under its own identity, escalates judgment calls to a human when it needs them, and leaves a signed record of every action it takes. This is different from a chatbot (which responds to queries from its own interface) and from an agent (which executes autonomous pipelines with minimal human involvement). The distinction matters when you are picking a tool or deciding what to build.
Chatbot, agent, coworker: what actually separates them
A chatbot lives inside its own surface. You navigate to it, ask something, get an answer, and leave. It has no persistent presence in your team's workspace — it doesn't own cards, it doesn't close tickets, and when you close the chat nothing changes in your project tool.
An agent executes pipelines autonomously. Given a goal and a set of permissions, it runs a sequence of steps — scraping, summarizing, sending — often without a visible presence in your shared workspace. Agents are powerful when the happy path is clear and errors are recoverable at low cost. They fit less naturally when you need to know exactly what happened, and when.
An AI coworker has a presence in your shared workspace the way a human teammate does. It has an account, an avatar in the activity feed, and tasks it owns. When it acts, those actions are attributed to it by name. When it hits something that requires judgment, it escalates rather than guessing. When it finishes, the results appear in your workspace — not in a separate interface you have to go check.
Three properties that define a real AI coworker
Most products claiming "AI coworker" have one or two of these. Real coworker behavior requires all three.
1. A desk — persistent presence in the workspace. The AI's tasks, standing instructions, and history live in the same tool as your team's work. You can see what it is doing without opening a chat window. You can leave it work before you go offline and review the results when you return. The state lives in the workspace, not in a conversation log.
2. Attribution — signed edits. Every action the AI takes — creating a card, moving it, writing a comment — carries its name and a timestamp. If you use Claude and ChatGPT on the same board, each carries its own identity and badge. There is no "system" actor making silent changes. A year from now, you can tell exactly which actions were taken by a human and which by which AI.
3. Escalation — judgment calls return to humans. The AI doesn't act when it isn't confident. It surfaces a small request — "approve, request changes, or reject" — and waits for your decision. Over time, as you calibrate its standing instructions, it escalates less often. The contract stays: decisions that require taste or context belong to humans.
The desk-and-office model
A useful way to think about how an AI coworker operates: the desk and the office are two distinct surfaces.
The desk is your project management tool — the AI's persistent workspace. Its task list lives there. Its progress shows there. When you are not in an active conversation with it, this is where its state lives.
The office is the AI's native app — Claude.ai, ChatGPT — where you go to hand it complex context, redirect its work, or give it a standing instruction. You talk to it in the office; it works at the desk.
MCP (Model Context Protocol) is the channel connecting the two. The AI in the office reads and writes the desk through MCP tools, and the results appear in your shared workspace. This matters for one technical reason worth stating plainly: MCP is pull, not push. The AI works when you — or a scheduled prompt you set up — trigger it. It does not continuously watch your board and act autonomously. "Always-on" is a useful shorthand but more accurate is "always-available, triggered on demand." This is intentional: unsupervised writes to a live board, with no approval gate, is not a safe default.
Where the coworker model fits — and where it doesn't
This model works well when your team runs real project work with tasks, status, and owners — not just documents. When you want visibility into what the AI did, not just the output it produced. When some decisions need human judgment and you want those to surface clearly rather than silently.
It fits less naturally when you need a fully headless pipeline with no human checkpoints. Or when the work is primarily document creation or research synthesis — an AI assistant is the better fit there. Or when the work is simple and repeatable enough that a pre-defined automation rule handles it without AI reasoning at all.
The honest limit: an AI coworker is only as useful as the structure of your workspace. A clear board with well-defined cards and explicit ownership produces useful AI contributions. A messy, undefined board produces noisy output regardless of the model quality.
Is an AI coworker the same as an AI agent?
Not quite. An agent typically runs in its own runtime and executes autonomous pipelines. A coworker operates inside a shared human workspace with attributed actions, its own identity, and a human approval path for judgment calls. Some agents can behave like coworkers — most don't.
Does an AI coworker work 24/7?
It works when triggered — by you directly, or by a scheduled prompt you configure. It doesn't continuously poll your board. The result is the same: work gets done while you're away. The mechanism is on-demand, not always-running.
What does "attributed edits" mean in practice?
Every action the AI takes carries a badge with its name and a timestamp in the board's activity feed. If you have multiple AI models working on the same board, each appears with its own identity. Nothing is attributed to "system" or silently added to your account.
Which tools have a real AI coworker?
Comuna was built specifically around this model: Claude and ChatGPT connect via MCP and become real board members — with attributed edits, an escalation flow, a daily brief, and zero per-seat cost. Most project management tools offer AI as a chat sidebar or an automation engine, not as a workspace member with its own identity. See AI coworkers vs AI chatbots for a longer look at why that distinction compounds, or browse the full feature set.
Comuna is free forever — no credit card, bring your own AI. Spin up a workspace and try it.