What are "Gemini agents"?

Google ships agent capabilities across its Gemini and cloud platforms — from assistant-style activity to developer and enterprise agent tooling. The packaging and names change, so this page compares at category level and points to Google's own documentation for the current state of play.

How do Dots differ from Google's agents?

A Dot is an always-on, identity-bearing agent inside OpenAI's ecosystem: you name a primary Dot, it has its own cloud computer and browser, learns from feedback over time, connects to 4,000+ apps, and you reach it through ChatGPT, Slack and Teams. Google's agent offerings are spread across its assistant and cloud/developer products, and are generally organised around Google's own ecosystem. Which suits you depends on where your work lives.

Which has more app integrations?

OpenAI says Dots can connect to more than 4,000 apps through its plugin ecosystem. Google's integrations differ and evolve; the honest comparison is to list the systems you actually use and check them against each vendor's current documentation, rather than rely on a count.

Should a Google Workspace team pick Gemini over Dots?

It depends. If your work is deeply embedded in Google's products, an agent built around that ecosystem is a reasonable default. If you want an always-on agent that reaches you through ChatGPT, Slack and Teams and owns ongoing work, a Dot is built for that. Review consequential output either way — agents, including Dots, can make mistakes.

OpenAI Dots vs Gemini Agents

Google's agent strategy and OpenAI's Dots are both attempts to make AI act, not just answer — but they are organised differently. OpenAI Dots are a single, named, always-on product inside ChatGPT. Google's agent capabilities are distributed across its assistant, cloud and developer platforms, and their packaging moves quickly. So this comparison stays at category level and points to Google's developer documentation for specifics.

Dots details below are drawn only from OpenAI's launch materials; anything unpublished is marked as such. We do not restate competitor models, prices or feature counts, because those are the vendor's to state and they change.

Two ways to organise an agent

OpenAI's design puts one persistent agent at the centre. You start with a primary Dot and give it a name; it has its own isolated cloud computer and browser, connects to 4,000+ apps through OpenAI's plugin ecosystem, learns from your feedback over time, and works 24/7. You reach it through ChatGPT on desktop, web and mobile, and through Slack and Teams. The product is the agent.

Google's approach tends to be platform-shaped: agent capability appears within the assistant you already use and within developer and enterprise surfaces. That means the "agent" may look very different depending on whether you meet it in a consumer assistant or in a cloud workflow. Neither structure is inherently better; they optimise for different starting points.

Distribution and reach

Distribution is where the difference is easiest to see. Dots inherit ChatGPT's surfaces and add Slack and Teams, with texting on a limited Pro waitlist. A Google-centric agent inherits Google's surfaces. If your organisation lives in Google Workspace, that inheritance is an advantage; if it lives in ChatGPT and Slack, Dots' reach is the advantage. This is usually a stronger deciding factor than any feature checklist.

Identity, connectivity and governance

For organizations, OpenAI states that specialist Dots have their own identity, credentials, and access to systems of record, and that these are being integrated with enterprise governance via Microsoft Agent 365. On the Dots side, background research is read-only, actions pass through auto-review against instructions and Custom Rules, and there is an activity view; our security & privacy guide has the detail. Google publishes its own governance and access model for its agent products — consult the vendor rather than assume parity.

Side by side

Dimension	OpenAI Dots	Gemini agents (category)
Runs where	Its own isolated cloud computer with a browser, 24/7	Across Google's assistant and cloud/developer surfaces; confirm current details.
Model	GPT-6 Astra	Google's own Gemini models; versions change — check the vendor.
Identity / credentials	Named Dot; specialist Dots have their own identity and systems access	Defined by Google's identity and cloud model; verify in its docs.
App connectivity	4,000+ apps via OpenAI's plugin ecosystem	Google ecosystem plus integrations; coverage evolves.
Approvals / governance	Read-only research, auto-review, Custom Rules, activity view; can be paused	Google's published controls and admin policies; check the vendor.
Best fit	Ongoing work reached through ChatGPT, Slack and Teams	Work already anchored in Google's products and platforms.
Primary source	OpenAI, Introducing dots	Google's documentation

What to verify before you commit

Where the agent runs — a Dot works on its own cloud computer; check whether a given Google agent runs in the assistant, your cloud project, or both.
How it is reached — the channels your team already uses decide how much new surface area you add.
Governance — for enterprises, ask who can grant, review and revoke an agent's access, and whether it fits your existing controls.
Cost model — Dots are included with eligible Pro and Business Premium plans, with extra-Dot pricing not published; see Dots pricing. Compare against Google's current plans directly.

It depends on your needs

There is no universal winner here. Choose Dots for a persistent, named agent that lives where you chat and collaborates across channels and apps. Lean toward Google's agent offerings when your work is anchored in Google's ecosystem and you value that integration. Many organisations will end up with more than one agent, split by department and tooling.

Whatever you choose, treat autonomous work carefully: define what may run unattended and review consequential output, because agents — Dots included — can make mistakes.

Source for Dots facts: OpenAI, Introducing dots. Independent guide; not affiliated with OpenAI or Google.