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OpenAI research shows workers crossing job boundaries with AI, and it matters for crypto labor markets too

OpenAI research shows non-developers are using its Codex AI agent to perform engineering tasks, with token consumption surging 137-fold among individual users and 189-fold among groups between August 2025 and June 2026. Over 25% of Codex work by business-function employees involved engineering or coding tasks, and 99.8% of weekly output tokens flowed through Codex by June 2026, raising concentration risks for crypto companies relying on AI-augmented workflows.

read2 min views1 publishedJul 27, 2026
OpenAI research shows workers crossing job boundaries with AI, and it matters for crypto labor markets too
Image: Cryptobriefing (auto-discovered)

Via openai.com

Non-developers are now doing engineering tasks with AI agents, raising big questions about how decentralized teams and crypto companies will restructure.

Legal teams writing code. Recruiters building engineering workflows. Finance departments tackling tasks that used to require a CS degree. OpenAI’s latest research, released June 25, shows that its agentic AI tool Codex isn’t just making workers faster. It’s making them do entirely different jobs.

The numbers behind the blur #

OpenAI’s Economic Research team tracked Codex usage between August 2025 and June 2026. Non-developer token consumption surged 137-fold among individual users and 189-fold among groups. By June 2026, Codex accounted for 99.8% of all weekly output tokens.

Over 25% of Codex work performed by business-function employees involved engineering or coding tasks. People in Legal, Finance, and Recruiting were effectively crossing into technical territory that would have required hiring a developer just a year earlier.

About 80.6% of surveyed users made at least one Codex request estimated at over 30 minutes of equivalent human work. Roughly 25.6% of users exceeded eight hours in delegated task time.

OpenAI’s April 2026 “AI Jobs Transition Framework” categorized occupations by vulnerability to automation and found that AI can theoretically handle around 90% of tasks in the highest-risk roles. But actual usage was considerably lower, with workers engaging AI tools for less than a quarter of that theoretical potential.

A June 2026 EU framework extension noted that Europe has lower shares of high-automation-risk employment compared to the US. That geographic divergence matters for crypto companies deciding where to locate talent and operations.

When 99.8% of output tokens flow through a single vendor’s agent, that’s a concentration risk. Projects building on AI-augmented workflows need to consider what happens when the API goes down, the pricing model changes, or the model’s outputs degrade.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our

Editorial Policy.

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