AI Coworker Agents, Compared: What the New Workplace Agents Actually Do
The chatbot that sat in a sidebar waiting for your questions is becoming an agent that lives inside your tools — drafting the email, updating the spreadsheet, chasing the follow-up. Google, OpenAI, Meta and Anthropic are all racing to build these "coworker agents." Here's what they can actually do, how the options differ, and what to watch out for before handing one real work.
Coworker agents from Google, OpenAI, Meta and Anthropic all promise the same thing: AI that acts inside your workplace tools instead of just chatting. The practical differences come down to which apps your team already lives in. They're genuinely useful for repetitive, multi-step admin work — but unreliable enough that anything important needs a human check. Start with low-stakes tasks and require approval before anything leaves the building.
What a "coworker agent" actually is
A chatbot answers questions when you ask. A copilot suggests things inline as you work. An agent takes a goal and runs with it: "prep me for the 2pm client meeting" becomes a calendar check, a scan of recent email with that client, a summary of what was promised last time, and a draft agenda — all before you've opened a second tab.
The new wave connects directly to business systems rather than just browsing the web. Google's version can be set up as a dedicated "coworker agent" with its own email address — you CC it on a thread like a colleague, and it picks up the work. Less like a tool you open, more like a junior colleague you delegate to.
What they can do today
Email triage and drafting. The strongest use case: read a long thread, summarize what was decided, draft a reply in your voice for your review. The weak spot is tone judgment — it can't tell when a client needs a softer touch.
Meeting prep and follow-up. Pull the invite, find relevant docs and prior notes, assemble a brief; afterward, turn notes into action items and file them. Works well because it's mostly reorganizing information that already exists.
Spreadsheet maintenance. Updating sheets, reconciling lists, flagging mismatches — decent when the rules are explicit, shaky when matching requires judgment calls.
Scheduling. With calendar, email and chat visible at once, agents handle the back-and-forth: propose times, email attendees, update invites. One with its own email address keeps working the thread unwatched.
Research briefs. "Pull together what we know about this vendor" — searches your docs, email and the web, then compiles a briefing. Fine as a starting point; risky as a final answer, since it can blend real company data with something half-remembered.
The pattern: agents do best with structured, repetitive, multi-step work that's easy for a human to verify — summaries, drafts, lists, schedules. They do worst where a subtle mistake is expensive and hard to spot.
The main players compared
Four companies, same idea, four ecosystems. The ecosystem matters more than the feature list: an agent is only as useful as the tools it's allowed to touch.
Google — Gemini agent for work. Broadest reach: Gmail, Docs, Sheets, Calendar, plus Microsoft 365 and Slack. Standout: dedicated "coworker agents" with their own email addresses. Best for Google Workspace teams or mixed Google/Microsoft shops. google.com
OpenAI — Dots. OpenAI's entry for teams centered on the ChatGPT ecosystem: an agent that plans tasks, uses tools, and connects to business systems. Best for teams standardized on ChatGPT wanting the agent layer from the same vendor. openai.com
Meta — Muse. Meta's workplace agent for organizations deep in its ecosystem. Judge it like the others: by which of your apps it can reach, not by the demo. Best for teams already on Meta's workplace stack. meta.com
Anthropic — Claude for Google Workspace. Narrower and focused: Claude inside Docs, Sheets and Slides, in beta for paid users. Less a roam-everywhere agent, more a strong writer embedded where documents get made. Best for teams already paying for Claude. anthropic.com
Pick by where your data already lives, not by whose demo impressed you. An agent that reaches your email, calendar, docs and chat beats a "smarter" one that can't.
Who should care
Founders and tiny teams. Cheap leverage for inbox triage, scheduling, and spreadsheet upkeep. The catch: you're giving the agent the broadest access to your most sensitive data — read the privacy notes below twice.
Operations and admin staff. The biggest immediate winners. If your job is inbox, calendar, and follow-ups, an agent can take the repetitive middle while you keep the judgment calls. Start with one workflow, not five.
Managers. Meeting prep, status summaries, chasing action items. The value is never walking into a meeting cold or losing track of who promised what.
IT and security leads. Your teams will turn these on with or without you. Better to set data-access policies now than discover an agent CC'd on every client thread six months from now.
Who can wait: strictly regulated industries, until the compliance story is clearer — and anyone whose work rarely touches these app suites.
What to watch out for
Privacy and data access. An agent is useful because it sees a lot: email, calendar, documents, chat. Check what the provider can access, how long they retain it, and whether your inputs train their models. Business plans are usually stricter than consumer ones. Handle client data or NDAs? Get the data-processing terms in writing first.
Mistakes that look confident. Agents don't fail with error messages — they fail like a confident intern: a summary inventing a decision nobody made, an email referencing the wrong project, a spreadsheet with plausible but wrong numbers. The output always looks finished. Review isn't optional for anything external or financial.
Keep a human in the loop. Require approval for anything that leaves the building: sending email, posting messages, sharing documents externally, spending money. Leave approval gates on until the agent has handled a workflow correctly dozens of times, and check the activity log regularly.
Permission sprawl. An agent with its own email and broad access is a new employee with perfect memory and zero judgment. Review its permissions like a new hire's — and revoke them when people leave or projects end. Stale agent permissions are a security problem waiting to happen.
Lock-in. The deeper an agent embeds — its own email address, learned patterns, integrations — the harder it is to switch providers. Prefer exportable data, and think twice before building processes only one vendor's agent can run.
Frequently asked questions
Do I need a coworker agent if I already use a chatbot?
Not necessarily. A chatbot answers questions; an agent does multi-step work across apps. If your AI use is "draft this" or "summarize that," a chatbot is fine. An agent earns its keep on repetitive workflows spanning email, calendar, docs and chat — the handoffs are where the time savings live.
Will it make mistakes?
Yes. Treat agent output like a keen intern's first draft: often good, sometimes wrong in ways that look right. Never let it contact a client, publish, or touch money without human review. The review habit matters more than which agent you pick.
Is my data safe?
It depends on the provider, plan, and settings. Check admin controls, retention policy, and whether your content trains their models — business tiers are typically stricter. Rule of thumb: if you wouldn't paste it into a chatbot, don't grant an agent access to it either, until you've verified the terms.
How do I start safely?
Pick one low-stakes workflow — meeting prep, inbox summaries, scheduling. Start read-only if possible. Require approval for external actions. Watch the activity log for a couple of weeks, then expand. Boring is the point — it's how you avoid an embarrassing incident.
Workplace AI is moving from answering questions to doing work. The products are early, the demos beat the reality, and the ecosystem you already live in matters more than any feature comparison. For the right workflows — repetitive, multi-step, easy to verify — a coworker agent is already a genuinely useful colleague. Just remember which one of you is the senior.