OpenAI on July 27, 2026 released a research report arguing that artificial intelligence is not merely automating existing jobs but fundamentally redrawing the boundaries between them. Analyzing more than 800,000 messages from U.S. ChatGPT users, the company found that 43.5% of occupation-specific messages involved tasks traditionally associated with an entirely different role.

The report, titled Work at the Frontier: How AI is Expanding What People Do at Work, is the first installment in a new series examining how the technology is reshaping labor in real time. Axios reported the findings on July 27, noting that the data offers a rare window into a shift occurring before it shows up in job titles or descriptions. For more on how AI is transforming the workplace, see our AI industry coverage.

The Concept of 'Task Crossover'

OpenAI coined the term "task crossover" to describe work historically associated with one occupation appearing in the AI use of people in another. A salesperson uses AI to explore a customer dataset that once went to an analyst. A marketer troubleshoots a website without waiting for a developer. A small-business owner drafts copy, reviews a contract, or runs basic financial analysis.

"In each case, AI changes not just how work gets done, but who does what," the report states.

To isolate the phenomenon, researchers first separated "generic" activities — writing, summarizing, and scheduling — that are too broadly shared across occupations to signal crossover. Among the remaining occupation-specific messages, 43.5% fell outside the user's own field. Overall, 16.8% of all work-related messages concerned tasks tied to another occupation.

Which Roles Borrow the Most

The pattern is not evenly distributed. Once generic work is excluded, outside-occupation tasks account for striking shares of occupation-specific AI use:

  • 77% of messages from customer experience workers
  • 75% from designers
  • 69% from human resources workers
  • 56% from legal workers
  • 53% from marketers

These occupations are effectively "borrowing" tasks from other roles. The evidence, OpenAI argues, points to a changing division of labor in which activities that once required a handoff can now be completed by the person who first encounters the need.

Which Tasks Travel the Farthest

Marketing and engineering tasks travel the broadest across occupations, frequently surfacing in messages from workers outside those fields. Two activities — financial calculation and technology troubleshooting — appear among the three most common outside tasks in all seven other occupation groups studied.

The analysis also reveals two distinct directions of crossover. Design illustrates the inward pattern: about 35.2% of messages from designers involve work from another occupation, yet design tasks account for only 1.7% of messages from workers in other fields. Designers draw heavily on outside tasks, but design work itself rarely migrates elsewhere.

Engineering is closer to the reverse. Only 18.5% of engineering messages involve tasks from other fields, but engineering tasks account for 7.4% of messages among workers elsewhere — making it an important source of work that people in other roles take on, from software troubleshooting to managing technical systems. Marketing stands out in both directions. Marketers devote 24.3% of their messages to other occupations' tasks, while marketing tasks account for 8.9% of messages from workers in other fields — the highest outward share in the sample.

A Companion Framework for Job Transitions

The report accompanies OpenAI's AI Jobs Transition Framework, a separate document in which the company argues that many jobs are likely to reorganize because their day-to-day tasks could change substantially with AI assistance. Together, the two pieces position OpenAI as both a participant in and an observer of the labor disruption its own products are driving.

The company said it would publish regular data-driven insights from this vantage point to guide policy and practice. "Using our unique window into how the world of work is changing," OpenAI wrote, "we will offer regular data-driven insights based on evidence."

Why the Findings Matter

Most studies of AI and work begin with a fixed list of tasks for a given occupation and ask whether models can perform them. OpenAI's evidence suggests the more consequential shift may be in who takes on which tasks — a redistribution of work that happens informally, through individual AI use, long before employers reorganize teams or rewrite job descriptions.

The implications are significant. If workers routinely perform work that once belonged to other roles, the boundaries that define professions, departments, and even compensation structures could blur. That raises urgent questions about training, accountability, and how organizations value work that no longer fits neatly into a single job category.

The findings also complicate the common framing of AI as a tool that simply replaces or augments a specific job. Instead, they suggest a more fluid dynamic in which AI enables a marketer to do engineering, a designer to do finance, and a customer-experience worker to do legal research — collapsing the walls between roles that organizations have spent decades building.

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