AI agents are creating more work, not less — and OpenAI’s own numbers back it up

OpenAI says it hit a goal it set last fall, stating researchers are now using what the company calls an “automated research intern,” which is an agent that can handle well-defined tasks that would normally take a researcher several days.

The data shows coding-agent use climbing throughout 2026, and by mid-August its agents were logging 3.1 agent-workdays for every human workday across the research organization. The median researcher was spending more than $600 on inference per day at API prices, while those in the 90th percentile spent more than $7,000.

The median researcher was spending more than $600 on inference per day at API prices, while those in the 90th percentile spent more than $7,000.

Agent hours versus useful output

But everyone knows that an agent-workday and a human workday aren’t the same. The company converts the time agents spend working on tasks into standard eight-hour workdays. Because researchers can run several agents at once, the figure tells us how long the agents are working, but not necessarily what they’re completing.

For engineering teams, that leaves plenty of work on the human side, which means running more agents can increase the amount of work happening at once, but it can also increase the amount of work a human needs to keep track of.