Zapier Agents vs. ChatGPT workspace agents: What's the difference?

Wasn't AI supposed to swoop in and save the workday by giving us all less to do? I don't know about you, but writing prompts and refining them (and refining them…again) is giving me more work than I had in the pre-AI ages.

That's why I try to build agents whenever I can. But choosing the right platform to build them on matters just as much as deciding to use them in the first place.

OpenAI is rolling out its Codex-powered version of AI agents, called workspace agents. They're a lot like Zapier Agents, with some key differences. Here's what we know so far about how they compare.

Table of contents:

• Zapier Agents vs. ChatGPT workspace agents at a glance

• Both make agent-building easy, but Zapier lets you build full business systems

• Both let you standardize how agents work, but Zapier has a deterministic layer

• Zapier connects to significantly more apps

• Zapier Agents come with more AI model flexibility

• Zapier supports stronger governance

• Which should you choose?

Zapier Agents vs. ChatGPT workspace agents at a glance

Both make agent-building easy for everyone, but Zapier lets you build end-to-end business systems

To build a ChatGPT workspace agent, you'd start by going to the ChatGPT sidebar. You click Agents, then Create, and then type in a prompt describing your desired agent behavior. After ChatGPT thinks on it, you'll get a plan for the agent's instructions that you can either approve or tweak. And from there, you'd connect your tools and set the agent loose.

You can also deploy workspace agents directly in Slack, where they can pick up requests from teammates, answer questions, and kick off workflows without anyone leaving the conversation.

In Zapier, you can access agents from the dashboard, where you can also see analytics, version history, and any agents you've grouped by "pods." To start building, just click + New Agent. Zapier Copilot, the built-in AI assistant, will ask you what you're looking for and then fulfill your wish.

Zapier Copilot can connect your agent to other Zapier products, too, like Zaps, Tables, and Forms. That means you can build end-to-end business systems—from the agent itself to the workflows, databases, and forms that power it—all under one roof.

And if you'd rather talk to your agent without leaving the tab you're working in, the Zapier Chrome extension puts it right in your browser.

Both Zapier and ChatGPT let you spin up agents with templates. OpenAI released a set of them for common back-office workflows. At Zapier, we've been curating battle-tested agent templates for over a year now, including templates our own teammates created and rely on to this day.

Two of our most popular Agents templates are the Support Email Agent, which drafts replies to your customers by looking up answers from your knowledge base, and the Lead Enrichment Agent, which researches new leads for you, enriches them with key details like job title and company size, and updates your CRM automatically. For more templates, visit the Zapier Agents template library.

Both let you standardize how agents work, but Zapier also offers a deterministic layer

Like other AI coding tools, ChatGPT lets you add skills to your workspace agents: reusable, shareable workflows packaged as a Markdown file (or a folder of them) with instructions, examples, and sometimes code. The point is to teach an agent your team's playbook once—say, the exact way you format QBR decks or the steps your finance team follows for vendor onboarding—and then reuse that skill anywhere, without rewriting the prompt every time you build a new agent.

Eventually, you'll be able to convert any existing GPTs you have into workspace agents, too.

If you want something even more deterministic—leaning on rules instead of strong recommendations—you have a few options:

• Build a Zap. Zaps are deterministic workflows that run the same way every time.

• Weave a Zapier agent into a Zap. That gives you the reliability of a deterministic workflow with added AI judgment in the middle.

• Have one Zapier agent call another. Agents work best when given specific jobs. With agent-to-agent calling, you can chain specialists together so each one handles the part it's trained to do.

Zapier Agents connects to significantly more apps (about 9,000 more)

OpenAI says that beyond the usual suspects—Gmail, Google Drive and Calendar, Outlook, SharePoint, GitHub, HubSpot—more connectors for agent workspaces are on the way. But if you want to build a workflow right now on an app they don't support yet, you're out of luck. Technically, you can wire something up through MCP. But that means standing up your own MCP server or finding a third-party one, then managing the connection yourself.

If you're set on sticking with workspace agents, you could simplify this with Zapier MCP, which gives ChatGPT access to Zapier's 9,000+ app integrations through a single connection. At that point, though, you're adding Zapier to fill the gap anyway.

Zapier already comes with more than 9,000 app integrations out of the box. One agent can read from your CRM, write to your project management tool, post to your team chat app, update a spreadsheet, send an email, file a ticket, and pull data from your billing system, no matter which apps you prefer. And someone with no coding experience can build all that with just a few clicks.

That breadth means teams across your entire organization can build agents that plug into the tools they already use, without waiting on IT to add a new connector. A workspace agent can only do the parts that touch OpenAI-supported tools.

Zapier Agents comes with more AI model flexibility

ChatGPT workspace agents run on Codex, which currently uses GPT-5.5 as its flagship model. And it's well-suited for the agentic tasks OpenAI designed it for. But if a different model would do the job better, cheaper, faster, or more accurately for your use case, you can't use it. Not easily, anyway. You could wire up another model by calling it as an external tool through MCP or your own API wrapper. But passing context across that boundary spends tokens. And once workspace agents move to credit-based pricing, you'll feel that cost on your bill.

Zapier Agents lets you access other models. Under the hood, the core agent runs on a single model. But you can bring other AI tools into the mix, calling ChatGPT, Claude, Gemini, or another model at specific steps in your agent's instructions. Agents is priced by "activities," and each tool call counts as one activity. So if your agent calls Gemini to summarize something, that's one activity, regardless of how long the thread is.

Credits, like ChatGPT will implement, work differently. They're based on input and output tokens, which means a longer prompt or response can drive your bill up, often in ways that are hard to predict before you run an agent.

Zapier Agents was built with governance from day one

Both ChatGPT workspace agents and Zapier Agents offer audit and compliance features. Zapier ships real-time SIEM streaming for automation events (that lets your security team see agent activity in their monitoring tools as it happens) as well as cross-product audit trails. ChatGPT Enterprise already has a Compliance API that surfaces agent configurations, updates, and run history. And an org-wide agent dashboard is coming soon.

Workspace agents have granular role-based access controls. There are separate toggles for who can browse, run, build, and publish agents. And admins can create named roles with their own permissions for which ChatGPT features each role can access. Zapier uses a fixed four-tier system: Owner, Super Admin, Admin, and Member.

But where Zapier's governance stands out is in its consistency. Every rule you set—which apps your team can connect to, what actions they're allowed to take inside those apps—applies everywhere: Zaps, Agents, and MCP-connected assistants. You set the policy once, and it holds across the board.

That matters because once your agents are doing things in other apps, your security is only as strong as the weakest link in your workflow. An admin might carefully restrict Salesforce record deletion inside a workflow but forget—or be unable—to restrict it for an agent or an MCP-connected assistant. That's where a security gap opens up. When your teams are building across multiple tools and each one has its own governance model (or none at all), gaps show up quickly.

Zapier also lets you control where your data goes during inference. If you're at a company with strict AI requirements, you can route agents through your own AWS Bedrock account—what's called Bring Your Own Model (BYOM)—so AI inference stays within your approved infrastructure. Zapier still handles the automation logic, but the model calls never leave your cloud contract. And if you're security-conscious enough to hold your own encryption keys, ChatGPT workspace agents aren't available to you at all right now.

ChatGPT workspace agents vs. Zapier: Which should you choose?

If your teammates are heavy ChatGPT users, your tool footprint is small, you're comfortable being on OpenAI models, and you're ok running on a research preview product, ChatGPT workspace agents are a solid choice.

But if you need agents that can reach across the apps you use, run tasks on whatever model fits the job, and operate inside a governance framework that's already approved by your security team, pick Zapier Agents. You'll be joining 200,000 builders who have created over 450,000 agents, completing more than 33 million activities to date.

For a closer look at how Agents works, check out the feature guide. You'll find a walkthrough on setup, real use cases, and tips for getting the most out of an agent once it's running. If you're eager to just start building, head straight to the Agents dashboard.

Related reading:

• AI Guardrails: Add safety and compliance checks to your workflows

• Zapier MCP: Perform tens of thousands of actions in your AI tool

• Zapier SDK: Run app actions directly from your code