OpenAI introduces Dots to ChatGPT: GPT-6 Astra-based agents with their own cloud computer, access to authorized applications, and the ability to perform ongoing tasks even between conversations.
OpenAI is adding a new category of agents to ChatGPT called Dots.
The news appears in the release notes of the September 29, 2026 and is rolling out progressively to some Pro, Business Premium, and Enterprise users.
The difference compared to a normal conversation with ChatGPT is significant.
A Dot isn't just meant to receive a request, produce a response, and finish the job. OpenAI describes it as a always-on agent, that is, an always-available agent who can be entrusted with a continuous objective.
What are OpenAI Dots?
A Dot is a personal AI agent available within ChatGPT.
According to the official documentation, each Dot has:
- one of its own cloud computing;
- access to applications that the user decides to connect;
- memory of the context useful for work;
- ability to carry out complex activities over time;
- ability to ask for user intervention when a decision is needed.
The system is powered by GPT-6 Astra, the model that OpenAI introduced in September 2026 with advanced capabilities for computer use, browsing, coding, and multi-step work.
The relevant transition is therefore this: from a chat used on demand to an agent who can be assigned responsibility.
What is the difference between a Dot and a regular chat?
In a traditional conversation, the user maintains direct control of the flow.
He's asking for something.
He gets a response.
If necessary, correct or add information.
A Dot, on the other hand, is configured with a goal and a certain level of autonomy.
OpenAI explains that it can understand what steps are needed, use the tools provided, and continue the work, reporting the results back to the user when review or decision-making is needed.
The change therefore mainly concerns the continuity.
You no longer need to re-type the same task every time you reopen ChatGPT.
An AI agent can work across multiple applications
One of the core elements of Dots is the ability to use connected applications.
OpenAI describes the Dot as an agent that can work “across the apps you choose to connect,” that is, through the tools authorized by the user.
This opens up very different scenarios than simply generating text.
An agent could, for example, collect information from multiple services, update documents, organize tasks, or prepare the output of a multi-step process.
The important point is that the Dot has its own operating environment in the cloud.
It therefore does not limit itself to explaining what should be done: it can concretely use tools and applications available within the authorised perimeter.
The real difference is moving from a task to a responsibility
“Write this email” is a task.
“Manage the follow-up of this project and bring me decisions that require my intervention” is a broader responsibility.
This is the kind of change that the Dots make most evident.
A continuous agent can be especially useful when the job does not end with a single output, but requires multiple steps spread over time.
For a company, activities such as:
- collect information periodically;
- keep a project up to date;
- prepare materials from new information;
- coordinate steps between multiple instruments;
- highlight situations that require a human decision.
Technology alone, however, does not solve the organization of the process.
Before delegating, it is necessary to define what the agent can do
Entrusting responsibility to an autonomous system requires more precise rules than simply asking for a draft.
A business activity often contains exceptions that people know about but have never formalized.
A sales manager might know that:
- above a certain amount an authorization is required;
- some customers have different conditions;
- certain promises should not be made;
- Some information needs to be verified before submission.
For an experienced person these rules may be implicit.
For an agent they must become readable.
Before delegating a process it is therefore useful to establish:
- what information you can consult;
- what actions it can perform autonomously;
- when you need to ask for confirmation;
- which cases must always be handled by one person;
- what “job completed” actually means.
AI agents are also changing the way we measure time savings.
With a chatbot the result is immediately visible.
With a continuous agent the evaluation must be broader.
It is not enough to measure how quickly it produces a response.
It should be noted:
- how many manual tasks it eliminates;
- how many checks remain necessary;
- how many errors or corrective interventions it introduces;
- how long does supervision take;
- if the end result really comes faster.
An agent that produces a lot of work but takes just as long to control is not necessarily improving the process.
The correct parameter remains the time needed to reach an approved result.
Are OpenAI Dots available in Italy?
To the October 1, 2026, availability is still limited.
OpenAI says Dots is rolling out to users Pro, but at launch Pro access does not include the European Economic Area, Switzerland and the United Kingdom.
This means that a Pro user in Italy is currently not included in the initial distribution.
The situation is different for Business Premium, where OpenAI indicates availability in supported ChatGPT regions, and for Enterprise, where a beta phase is planned that can be activated by workspace administrators.
Availability therefore depends on the plan, geography and workspace configuration.
OpenAI Dots and the Growth of AI Agents
Dots fits into a broader market direction.
OpenAI also introduced new agent-dedicated infrastructures in the same period, including the Agents API, announced on September 10, 2026.
Change is no longer just about models capable of generating better content.
The competition is shifting towards systems capable of:
- use tools;
- move between applications;
- maintain context;
- perform multiple steps;
- work with greater autonomy.
For companies, this means starting to evaluate AI not just as a production tool, but as a potential component of operational processes.
What this means for your business
Before introducing an AI agent, it is a good idea to identify the tasks that currently require continuous manual steps.
For example:
- open multiple tools to complete a single task;
- copy information from one system to another;
- repeat the same checks over and over again;
- periodically update documents or reports;
- gather information before making a decision.
From there, you can understand whether you really need an agent, simpler automation, or better integration between the software you already use.
The goal shouldn't be “use an AI agent.”.
It should reduce unnecessary steps while maintaining control, auditability and accountability over decisions.
DigiFe develops AI solutions for business starting from the company's real processes, identifying where agents, automations and integrations can create a concrete operational advantage.
