OpenAI Wants AI Agents to Run Your Workday. Can It Convince Anyone Beyond Coders?

Key points

• OpenAI launched ChatGPT Work last month, available on its $20-per-month subscription plan.
• An OpenAI-backed study found that in June 2025, fewer than 1% of individual subscribers were using Codex, the agentic coding tool ChatGPT Work grew from.
• The desktop app currently has around 20 million users, versus more than one billion people who use ChatGPT through a web browser.
• OpenAI's lead desktop engineer has given the app full access to his inbox, Slack, Notion, and Figma to test it properly.
• Vertical AI competitors such as Harvey (for lawyers) and Clay (for sales teams) are already chasing professional users with a focused approach.

Andrew Ambrosino has handed a piece of software the keys to almost everything. His inbox. His Slack messages. Apps he uses to design and plan. As lead engineer for OpenAI's desktop app, he granted the program access to all of it, not because he has no concerns, but because he thinks it is the only honest way to stress-test what he is building.

"If I'm asking it to write a document, is there a possibility that it's going to pull from a private DM on that subject and not know that it's not supposed to share some info? Yes," Ambrosino told TechCrunch AI. "I'll do it for the job."

That product is ChatGPT Work, released last month and included in OpenAI's $20-per-month subscription. It is built on top of Codex, which was originally a coding assistant. The idea now is to extend that kind of help to people whose jobs have nothing to do with writing software: accountants, investors, operations managers, finance teams.

What does ChatGPT Work actually do?

Think of it as a digital assistant that does not just answer questions but completes whole tasks on your behalf. It can scan a Slack conversation about an engineering problem and produce charts. It can pull together relevant emails and research into a polished investment memo. OpenAI says its own employees are using it to set up weekly metrics reports automatically.

The key concept here is an AI agent, which is software that can carry out multi-step tasks on its own without you clicking through each step. You describe what you want; the agent figures out which tools to open, what information to pull, and what to produce.

One engineer at OpenAI described asking the tool to look at a Slack conversation and "make some charts," then receiving back a series of genuinely useful plots. Sam Altman, OpenAI's chief executive, is apparently using it to plan holidays.

Why aren't more people using it?

The numbers tell a stark story. Inside OpenAI, 98% of employees were using Codex by June 2025. Among paying individual subscribers outside the company, that figure dropped to less than 1%.

Part of the gap is design. Early versions of Codex were built for software engineers and showed non-coders raw technical outputs that meant nothing to them. OpenAI has spent months reworking the experience so that ordinary workers can understand what the tool is doing and why.

Ambrosino compares the current interface to skeuomorphism, the old design trick of making a digital calculator look like a plastic one. It felt unnecessary once people got comfortable with touchscreens, but the familiar shape helped millions of people make the leap in the first place. Buttons that power users consider obvious, he argues, matter enormously when most people have never tried anything like this before.

"Without these products in front of the model, experts would know how to get the same results, but you wouldn't get to a billion people using the thing," Ambrosino said.

What does this mean for workers?

For now, OpenAI is pitching ChatGPT Work at repetitive, data-heavy coordination jobs: turning a spreadsheet into a live planning tool, assembling weekly reports that used to take an hour, summarising long Slack threads into action points.

For the average office worker drowning in messages and documents, that is a genuinely useful pitch. But granting an AI agent access to your inbox and work accounts is a real decision with real trade-offs. Ambrosino acknowledges the risk of private information surfacing in the wrong context. His advice, implied by his own approach, is to start with lower-stakes tasks and watch carefully what the tool does before widening its access.

OpenAI's commercial logic is straightforward: the longer an agent works on a task, the more it earns for the company. Reaching nurses, teachers, and shop owners matters far more to OpenAI's long-term finances than perfecting tools for the small slice of workers who write code for a living.