The Shift to Agentic AI: Evidence from Codex

2026-06-25

AI Summary

This study investigates how agentic AI is transforming work practices among non-developer users. Leveraging large-scale real-world usage data from OpenAI Codex, we construct a privacy-preserving automated analysis pipeline to compare behavioral logs, task complexity, and output metrics across three user groups: individual users, organizational users, and internal employees. Our analysis reveals the rapid adoption of agentic AI both within and beyond organizations: active users grew more than fivefold in the first half of 2026; over 10% of users routinely manage three or more concurrent agents per week; 26.6% employ shared skills to construct complex workflows; and certain roles exhibit up to a 50-fold monthly increase in output token volume. These findings demonstrate a clear shift from simple interactions toward multi-agent collaboration, signaling a fundamental transformation in work paradigms.

Abstract

We analyze usage data from OpenAI's Codex tool to present large-scale evidence of how agentic AI technology, which can take actions on a user's behalf, changes how people work. We use an automated, privacy-protecting pipeline to contrast usage across three populations: external personal-account users, external organizational-account users, and workers within OpenAI. We find that agentic AI usage is growing rapidly: the number of active users has grown more than fivefold in the first half of 2026, with the most rapid increase occurring outside the initial audience of software developers. Uptake is uneven: within OpenAI, Codex usage is nearly universal and has largely replaced business usage of ChatGPT. We document a similar shift to agentic tooling outside OpenAI, particularly within organizations, although external adoption remains lower and more uneven. In addition to headline usage figures, we observe measures of sophistication, and find that a growing number of users have used Codex to change their workflows substantially. More than 10% of users manage three or more concurrent Codex agents at some point each week and that 26.6% use skills, which allow users to share instructions for complex workflows. Alongside these changes in usage practices, request complexity has increased: since the start of the year, the share of individual Codex users who submit at least one request for a task estimated to require more than eight hours for an experienced human to complete has increased nearly tenfold. Concurrently, output has grown rapidly -- in June 2026, the median OpenAI employee in a legal role generated 13 times more monthly output tokens across Codex and ChatGPT than they did in November 2025, while the median researcher generated more than 50 times as many. We conclude by discussing the implications of these patterns for productivity, job reorganization, and workforce restructuring.

Problem

• Agentic AI
• Work Transformation
• AI Adoption
• Productivity
• Workflow Change

Innovation

• agentic AI
• Codex
• workflow transformation
• AI adoption
• productivity measurement