Researched and written with ViktorChatGPT Teams is a great writing assistant. An AI employee does the work in your tools. Here is when each one actually fits, with named workflows.
Key Takeaways
- Choose by the work pattern, not a chat-versus-action label. ChatGPT Business includes ChatGPT Work for connected-tool work. OpenAI also offers shared workspace agents in research preview for Business, Enterprise, Edu and Teachers plans. Compare those options with how your team delegates ongoing work to an AI employee.
- Some teams will use both. ChatGPT Business includes connected-tool work, not just thinking and writing. Choose by the connections, permissions, recurring work and shared context your team needs.
- Tool access depends on setup. @ChatGPT can take actions when the connected tool supports them and the configured account has permission. Compare the actions and account permissions your workflow needs, not just the quality of a draft.
- Check approval behavior before delegating. @ChatGPT asks for approval before taking action in connected tools. With Viktor, sensitive actions wait for human approval.
- Cost-per-outcome is what matters. ChatGPT Business Standard costs $25 per seat on monthly billing; compare the usage costs and time saved by your actual workflow. An AI employee costs more but replaces hours of cross-tool work per week.
Why this question keeps coming up
Three weeks into rolling out an AI employee for our ops team, our CFO sent me a Slack message: "We are already paying for ChatGPT Teams. Why do we need this?"
It was a fair question. Then the same week, our head of growth sent me a different message: "ChatGPT cannot pause underperforming Google Ads. I need something that can."
Both are asking fair questions. Whether ChatGPT can pause a campaign depends on a connected tool that supports the change and an account with permission. The decision is which setup fits the work, not whether ChatGPT can act at all.
Anthropic's December 2024 engineering guide defines agents this way: "Agents are systems where LLMs dynamically direct their own processes and tool usage." That is a different shape of product from a chat interface, even if the underlying model is similar. That line no longer separates ChatGPT Business from AI employees. ChatGPT Work can carry out connected-tool work, and workspace agents are available in research preview for Business, Enterprise, Edu and Teachers plans. Compare how the products handle shared context, recurring work and approvals.
This post is the answer I wish I had sent both of them at the same time.
What is ChatGPT Teams?
ChatGPT Teams, now called ChatGPT Business, is OpenAI's business plan for ChatGPT. Around $25 per user per month. You get the same chat interface as the consumer product, plus admin controls, a shared workspace, and the promise that your data is not used to train models.
What it is good at: writing, editing, drafting, summarizing, explaining, brainstorming, code review (in chat), structured analysis on data you paste in.
ChatGPT Business is no longer only a writing surface. ChatGPT Work uses connected tools and can carry out multi-step work, and workspace agents can use connected apps and send email with configured permissions and approval. OpenAI calls workspace agents a research preview. For a workflow such as pulling Stripe figures, verify the actual connection and permissions rather than assuming it works, or that it cannot.
What is an AI employee?
An AI employee is software that lives where your team already works (Slack, Microsoft Teams), connects to your tools the way a real teammate would (with credentials, permissions, and audit logs), and executes tasks across them with human approval.
We covered the full definition in What Is an AI Coworker?. The short version: it does not just suggest. It acts.
When we say Viktor "connects to 9,800+ integrations," we mean it has real read and write access. It can pull last week's pipeline from HubSpot, compare it to the previous quarter, and post the comparison to a Slack channel. It can pause a campaign in Google Ads if it underperforms below a threshold you set. It can draft a customer reply in Pylon, wait for your approval, then send.
A real Slack request looks like this:
@viktor pull this week's MRR change from Stripe, compare against the same week last quarter, list the top 3 expansions and top 3 churns by customer, and post a draft summary in #revenue for me to review before it goes to the teamThis request combines billing data, historical context, a summary and a reviewed Slack post. Whether ChatGPT can carry out the whole workflow depends on its connected tools, the actions they support and the configured account's permissions. Compare that setup with how your team delegates and reviews the work in Viktor.
How do they actually compare?
Side by side, on real workflows we run every week:
Workflow | ChatGPT Business, including Work and workspace agents | AI employee (Viktor) |
|---|---|---|
Draft a customer reply | Yes; connected tools can provide context when authorized | Yes, reads the ticket directly from Pylon or Zendesk |
Send the customer reply | Workspace agents can send email with configured tools and approval; support-ticket actions depend on the connection | Yes, after human approval |
Summarize last week's revenue | Can use connected data; verify the required Stripe access and report | Yes, pulls from Stripe directly |
Pause underperforming Google Ads campaigns | Depends on a connected tool that supports the campaign change and an account with permission | Yes, after approval |
Brainstorm a positioning angle | Yes | Possible, but not the strength |
Refactor a function | Yes; code and connected tools can provide context | Yes, reads from your repo |
Open a pull request | Yes, with repository access and the required permissions | Yes, via GitHub |
Build a comparison deck for a board meeting | Can create slide decks, spreadsheets and PDFs | Full PDF or Excel deliverable |
Triage your inbox | Depends on authorized mail tools and instructions | Yes, drafts triage decisions |
Watch for new high-priority Linear issues | Work can watch for updates and run recurring work; verify the required Linear connection | Yes, runs on a schedule |
Compose a thoughtful blog post outline | Yes | Yes, pulls from your existing posts |
Decide which deal to call next | Can use connected context; verify the CRM connection and decision criteria | Yes, from CRM context |
ChatGPT Business now includes tool-using and recurring-work options. Compare the exact app actions, approval requirements and chat surfaces your team needs rather than treating ChatGPT as a text-only assistant. OpenAI calls workspace agents a research preview.
When should you choose ChatGPT Teams?
You are mostly looking for a better writing surface. Your team writes a lot of emails, decks, briefs, code, and you want a fast, smart, private place to do that work.
You mainly need writing and analysis in a familiar chat interface. You can start there without connecting tools, then add connections if the work needs them.
You want a low-friction rollout. Your team may already know how to use ChatGPT, even if connected-tool workflows need additional setup.
The price is right. $25 per seat per month is one of the better unit economics in software.
If this describes you, ChatGPT Teams is a great fit. We use it ourselves alongside Viktor.
When should you choose an AI employee instead?
You have repetitive cross-tool work that nobody owns. Weekly reporting, account auditing, ticket triage, ad campaign hygiene, candidate screening, expense reconciliation. Work that touches three or more tools and happens on a schedule.
You want execution, not just drafts. You are tired of the pattern where AI gives you a great answer but you still have to go do the thing.
Your team works in Slack or Microsoft Teams and you do not want to add another tab. @ChatGPT now answers in Slack and Teams too, though it does not keep memory there. An AI employee shows up where conversations already happen, so adoption follows the path of least resistance.
You need an audit trail. Compliance, security, or your own peace of mind. OpenAI documents agent activity and workflow logs for @ChatGPT too. Compare the events recorded, who can review them and the retention your team needs before handing over the work.
If this describes you, you need an AI employee, not a chat window.
Should you have both?
Sometimes. Choose both when they solve different jobs for your team.
We do. ChatGPT Teams is open in a browser tab for our marketing team when they are writing. Viktor is in Slack for the work that touches Stripe, HubSpot, Linear, Notion, and the rest of the stack. Nobody is confused about which to use, because they are good at different things.
The mental model is similar to having both Google Docs and Notion. You could try to force everything into one. But you end up with bad workflows. Use each tool for what it is for.
What about ChatGPT plugins, GPTs, and the new "agents"?
OpenAI offers ChatGPT Work, custom GPTs and connected tools. It also offers shared workspace agents; its product page calls them a research preview for Business, Enterprise, Edu and Teachers plans.
A custom GPT that knows your style guide can be useful. But that is not the whole offering: ChatGPT Work supports connected-tool tasks and recurring work. Judge the workflow you need, not just the simplest GPT example.
This layer now runs scheduled and event-triggered Team Tasks in the cloud, and @ChatGPT answers in Slack and Teams. What @ChatGPT still lacks there is memory. A custom GPT with tool connections is not the same setup as shared, scheduled team work.
For work across ten tools, on a schedule, with human review and an audit trail, compare the supported connections, approval settings and logs. OpenAI documents those building blocks too. Check whether they cover your actual workflow before deciding which product should own it.
How does pricing actually compare?
ChatGPT Business: $25 per user per month, or $20 billed annually, for a Standard seat. You pay regardless of usage.
An AI employee (Viktor in our case): tiered pricing based on credits, which are consumed by actions. The more your team uses it, the more you pay. Most teams in the 10-50 person range land somewhere between $200 and $1,500 per month total, depending on use case density.
Compare the full bill, not just a seat price. ChatGPT Business has per-seat pricing, but OpenAI also prices workspace-agent runs in credits. For ongoing work, compare the seats and usage your workflow needs with the cost of the work it replaces.
A reasonable test: count the hours per week your team spends on cross-tool work that an AI employee could do. Multiply by your blended hourly cost. Compare to the AI employee price. We have seen this calculation come out clean above 5 hours per week of replaced work.
How does the trust model differ?
This is the part that does not show up in pricing pages and matters more than it should.
The trust boundary depends on what you connect, not just what you paste. ChatGPT Business can use connected tools and approved company context. For @ChatGPT in Slack and Teams, admins choose the company tools and access, and actions require approval.
An AI employee also needs access to the tools it will work in. Ask the same questions for either setup: which accounts are connected, what permissions do they have, who can approve changes, what do the logs show, and how do you revoke access when someone leaves?
For free-form chat with pasted data, the setup can stay simple. Once you connect tools, have the permissions and approval conversation before rollout. That applies to ChatGPT as well as an AI employee.
What about Microsoft Copilot?
Microsoft Copilot has a clear fit for teams working in Outlook, Word, Excel and Teams. But it is not limited to drafting inside Microsoft apps. Copilot connectors bring in external data, and Copilot Studio agents can use tools to act in other systems.
For a non-Microsoft stack, check the actual connection and action you need. Copilot Studio supports prebuilt connectors for Microsoft and non-Microsoft services, plus custom connectors and REST APIs. Access still depends on setup and permissions. Compare those requirements with how your team wants to delegate work, rather than assuming Copilot cannot reach outside Microsoft 365.
We compared a related product in Best AI Agents for Microsoft Teams.
Frequently Asked Questions
Will an AI employee replace ChatGPT Teams?
Not necessarily. Their jobs overlap, but teams may still prefer different setups for writing, shared context and ongoing tool work. Keep the tools that fit your workflows rather than assuming one must replace the other.
Can ChatGPT Teams pause my Google Ads?
It depends on the connected tool and permissions. @ChatGPT can take an action only when the tool supports it and the configured account has permission, and it asks for approval before acting. For Google Ads, check that the connected tool supports the campaign change you want.
Does an AI employee need my login passwords?
No. It uses OAuth or API keys with scoped permissions, the same way third-party tools you already use connect to your stack. We covered the security model in Is Your AI Agent Safe?.
What does the review-first model look like in practice?
You ask for an action. You see a draft of what will happen, including which tool will be touched and what the change will look like. You approve, edit, or reject. Only after approval does the action run.
Can ChatGPT Teams plug into Slack?
Yes. @ChatGPT answers in Slack and Microsoft Teams, though it does not record or access memory at launch. OpenAI also offers workspace agents in research preview: teams can share and use them in ChatGPT or Slack, with connected tools and memory. Availability and permissions depend on the plan, admin setup and agent configuration.
Related reading
Viktor is an AI employee that lives in Slack and Microsoft Teams, connects to 9,800+ integrations, and does the work, not just drafts about the work. Add Viktor to your workspace, free to start →
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