OpenAI introduces ChatGPT Work, a cloud-based AI agent that manages tasks across email, Slack and calendars

OpenAI on Thursday launched ChatGPT Work, a new AI agent embedded inside its flagship chatbot that aims to transform ChatGPT from a question-and-answer tool into an autonomous work platform capable of executing complex, multi-step tasks across users’ email, calendars, code repositories, and messaging apps.

The product is powered by OpenAI’s latest flagship model, GPT-5.6, and is designed to go far beyond generating text. ChatGPT Work can gather context from connected apps, files, and workflows to produce finished documents, spreadsheets, presentations, reports, and websites. The agent takes a stated outcome, breaks it into smaller steps, and stays with complex projects for hours, completing them independently.

The launch marks OpenAI’s clearest attempt yet to reposition ChatGPT as a workplace platform rather than a chatbot — and it arrives at a moment of extraordinary financial significance for the company. Last month, OpenAI confidentially submitted a draft S-1 registration statement to the SEC, initiating what could become one of the largest technology IPOs in history, with reported valuations clustering between $730 billion and $852 billion and annualized revenue that has blown past $25 billion.

In a short demonstration and conversation with VentureBeat on Friday, Ty Geri, a product manager at OpenAI who helped build ChatGPT Work, said the product’s mission is to democratize the kind of agentic AI capabilities that OpenAI’s internal engineering tool, Codex, has already demonstrated. «What’s really exciting is we’ve seen how much Codex has been able to push the frontier of what we can get done with these AI tools, as opposed to just getting information or answers or guidance,» Geri said. «Our internal adoption of Codex is literally an exponential curve across every single product function and every single use case.»

Why OpenAI built a persistent virtual machine that works from the beach

The core architectural bet behind ChatGPT Work is a persistent cloud-based virtual machine that runs on OpenAI’s servers, always available to the user regardless of which device they happen to be on. That marks a deliberate departure from competitors whose agents require a local machine to remain powered on and connected.

«What’s really exciting about ChatGPT Work is that it’s a virtual machine in the cloud that’s always on for you, and this is available across all of our paid tiers,» Geri said. «All Plus users are getting this. I think that’s a very unique aspect of this.»

The mobile-first aspect of the launch is something Geri described as «missing from the market.» He pointed to the ability to create a website on a phone and share it with collaborators as a particularly novel capability. «Sites are new in general to Codex. They launched in Codex about a week and a half ago, but now we’re launching also in web and mobile. You can create a site on your phone at the beach and share it with your friends,» he said.

ChatGPT Work will roll out beginning with Pro, Enterprise, and Edu users, and will expand to Plus and Business users over the next few days. In the interview, Geri emphasized that the availability of the product to Plus subscribers — not just premium tiers — is central to OpenAI’s strategy. «It’s accessible to all paid plans, including Plus users, which in my opinion is a really big feat, and really part of that OpenAI mission, which is about bringing all this power to as many people,» he said.

How MCP plugins connect ChatGPT Work to Slack, Gmail, and GitHub

The product relies on MCP-based plugins to connect to external services like Gmail, Google Calendar, Slack, and GitHub. When asked whether the plugin architecture is based on the Model Context Protocol standard, Geri confirmed: «These are all based on MCP.» He added that connecting multiple Gmail accounts — a frequent user request — «is definitely on the roadmap.»

The experience is designed to be action-oriented from the first interaction. ChatGPT Work offers a personalized onboarding flow that surfaces different suggested use cases depending on the user’s role. Geri demonstrated how the system, detecting his role as a product manager, immediately suggested tasks like evaluating AI systems, building research artifacts, and managing his calendar. «You can start with a simple task like catch me up on Slack or Teams or read today’s calendar,» Geri said. He described a scenario where the system reviewed his calendar, identified scheduling conflicts, flagged meetings requiring preparation, and then — on his instruction — declined, accepted, or rescheduled events directly.

Users can also customize the agent by teaching it their writing style, organizing outputs into projects, and — in a lighter touch — choosing a virtual pet that accompanies them in the interface. The interface also introduces a hosted website feature that allows users to build and share interactive sites directly through ChatGPT Work, turning what would typically be a static slide deck into a dynamic, collaborative artifact. «Now we suddenly have a collaborative interface that’s actually more exciting and more accessible than a slide deck, which has all these formatting restrictions,» Geri said.

Scheduling 10 bug bashes at once: what agentic productivity looks like in practice

Geri’s own usage of ChatGPT Work illustrates the breadth of tasks the system can handle. In the run-up to the product’s launch, he needed to organize pre-release testing sessions — known internally as «bug bashes» — across dozens of features and team members.

«I just come to ChatGPT Work and say, ‘Set up a bug bash for all the distinct features in ChatGPT Work. Add all the people that worked on that feature,’ and it can check Slack, it can check GitHub, it can check Docs, and find a time that works for the four highest contributors to that feature,» Geri said. «It went and scheduled 10 bug bashes, all coordinated across all those different people. That would have taken me 30 minutes at least.»

But Geri pushed back against the characterization that ChatGPT Work is limited to rote administrative work. He described using it for analytically complex tasks like identifying the biggest causes of user churn for specific product features and generating product solutions — work he said would previously have taken months. «Things that we would have spent three months doing, we can now spend a week doing — and do much more, and make a much better product,» Geri said. «Bugs that we would have found three or four weeks from now, we can now find within two days and fix for our users.»

He also described handing off the tedium of product testing itself. «It used to be that even though like the most interesting part of my job is like what to test, I would actually end up having to spend most of my job doing the testing, which is like me taking a mouse and like clicking on the same thing over and over again, like five times,» Geri said. «Instead, now I can define what do we want to test, and ChatGPT Work or Codex can actually go test it for me, deliver me that bug report, and then we can work on fixing that bug.»

What OpenAI says about data privacy when AI reads your Slack and email

When pressed on data privacy concerns — given that ChatGPT Work pulls sensitive information from workplace tools like Slack, Google Drive, and email — Geri said privacy «is incredibly important, and the most important part of this is it’s always in the user’s control.»

He pointed to OpenAI’s existing enterprise security infrastructure, noting that «enterprise accounts have ZDR, and users can always opt out of letting their conversations help improve future models, which many users do.» The comment aligns with assurances OpenAI made when it first launched ChatGPT Enterprise in August 2023, when the company wrote in a blog post that it does «not train on your business data or conversations.»

The privacy question carries additional weight now because of the sheer volume of sensitive workplace data ChatGPT Work is designed to access. Unlike a chatbot session where a user voluntarily pastes text into a prompt, ChatGPT Work actively reaches into connected systems — reading Slack messages, scanning calendar invitations, pulling GitHub commit histories — to assemble context for its tasks. That represents a fundamentally different data surface area than anything OpenAI has offered before, and one that enterprise security teams will scrutinize carefully before granting access.

ChatGPT Work enters a three-way arms race with Anthropic and Microsoft

ChatGPT Work lands squarely in the middle of what has become the defining competitive battlefield in enterprise AI: the race to build autonomous workplace agents that can go beyond generating text and actually execute tasks.

The product arrives months after Anthropic took Claude Cowork out of preview and into general availability in April, bringing its AI agent to web and mobile platforms aimed at helping enterprise users monitor and manage long-running AI-driven tasks from anywhere. Meanwhile, Microsoft made Copilot Cowork generally available worldwide on June 16, built in partnership with Anthropic to move beyond chat and into execution. The three products — ChatGPT Work, Claude Cowork, and Microsoft Copilot Cowork — now compete directly for the attention of enterprise IT departments and individual knowledge workers alike.

The convergence is striking. All three products share a remarkably similar vision: a persistent AI agent running in the cloud that can break complex tasks into steps, connect to workplace tools via plugins, and produce finished outputs rather than just conversational replies. All three work across desktop, web, and mobile.

What distinguishes OpenAI’s approach is its raw consumer distribution advantage. ChatGPT has reached 900 million weekly active users, and OpenAI now has 50 million paying subscribers. More than 9 million paying business users rely on ChatGPT for work, and 92% of Fortune 500 companies now use ChatGPT. By making ChatGPT Work available to Plus subscribers at $20 a month — not just Enterprise or Pro customers — OpenAI is betting that broad accessibility will drive adoption faster than any competitor can match.

OpenAI’s product manager says AI is a partner, not a replacement — with a caveat

When asked about the potential impact on the labor market, Geri was careful with his framing. He declined to speak broadly about workforce disruption but offered his personal experience as a product manager whose day-to-day work has been substantially reshaped by the tool.

«My job is not to schedule bug bashes and find out who contributed to a specific feature. That’s a task I do in my job, but that’s not my job,» Geri said. «My job is to make an amazing product.» He described ChatGPT Work as «a partner» and «an extension of me, certainly not a replacement,» adding: «Everybody feels far more productive than before, but is also almost working harder than before, because you get to work on all the things you want to work on as opposed to the drudgery around it.»

But Geri was also careful not to minimize the sophistication of the work the agent can handle. «I also don’t want to say that it’s only doing mundane tasks because, like something like hill climbing retention curves on a given feature is not mundane. It’s actually really hard to do,» he said. The distinction matters. If ChatGPT Work were merely automating calendar invitations and expense reports, it would be a convenience tool. The fact that Geri describes it compressing three months of analytical product work into a single week suggests something with far greater implications for how teams are structured and staffed.

An IPO-bound company needs ChatGPT Work to prove enterprise AI can generate revenue

The timing of ChatGPT Work’s launch is impossible to separate from OpenAI’s IPO trajectory. The company needs to demonstrate that it can convert its massive consumer user base into durable enterprise revenue — a narrative that becomes significantly more compelling with a product explicitly designed around professional workflows.

OpenAI said it is generating $2 billion in revenue per month, growing four times faster than Alphabet and Meta did at comparable stages, with enterprise now making up more than 40% of revenue and on track to reach parity with consumer by the end of 2026. But OpenAI remains heavily loss-making, and the company does not expect to reach profitability until around 2030, with internal projections suggesting losses of $14 billion in 2026 alone.

The competitive dynamics are unprecedented. Anthropic filed for its own IPO on June 1 at a $965 billion valuation, setting up simultaneous public listings from the two most prominent AI startups in history. Whether both can sustain their lofty valuations under the scrutiny of public market investors will depend in large part on whether products like ChatGPT Work and Claude Cowork deliver measurable productivity gains to paying enterprise customers.

The launch also caps a product trajectory that began with ChatGPT Enterprise in August 2023, accelerated through the release of OpenAI’s Operator agent in January 2025, and continued through Operator’s deprecation and shutdown on August 31, 2025, when its capabilities were folded into the ChatGPT agent framework. ChatGPT Work is the consolidation of those efforts into a single, unified product — one that pairs GPT-5.6’s three model variants (Sol for power, Luna for speed, and Terra for balanced everyday use) with a persistent cloud environment and an expanding library of MCP plugins.

The future of work may already be running in the cloud

When asked whether ChatGPT Work signals a shift toward a new kind of operating system — one where users interact with their computers primarily through an AI agent rather than through traditional mouse-and-keyboard interfaces — Geri stopped short of making sweeping predictions. But he hinted at the direction OpenAI sees ahead.

«Anybody who has worked with Codex or now ChatGPT Work will realize how exciting it is to interact with your environment and your computer via the agent,» he said. «Especially in the desktop app, where the model has access to your entire machine and can interact with websites on your behalf — it’s really able to be an extension of you and a real partner, and that certainly feels like the future.»

At the end of the interview, Geri circled back to something personal. «I’ve never enjoyed work as much as I have in the last month using ChatGPT Work and Codex,» he said — a striking admission from a product manager who, until recently, spent a meaningful share of his days clicking through the same interface five times in a row just to see if it would break. OpenAI is now asking 900 million users to believe that feeling scales. For a company weeks away from one of the largest public offerings in history, the answer to that question is worth roughly $850 billion.