Agentic Work Adoption

Agentic Work Adoption

Agentic work adoption is the measurable shift from using AI as a conversational assistant to using agents such as Codex to delegate, monitor, and review multi-step work.

Key points

  • OpenAI's public article frames Codex as a work-delegation interface, not only a coding assistant [src-169].
  • The underlying paper separates individual users, organizational users, and OpenAI workers so adoption is not treated as one blended number [src-170].
  • OpenAI workers are the frontier case: by June 11, 2026, Codex accounted for 99.8% of output tokens across Codex and ChatGPT for that population [src-170].
  • Organizational users show a weaker but still meaningful shift, with Codex at 63.3% of combined output tokens versus 16.5% among individual users [src-170].
  • The practical adoption markers are concurrency, skills, task complexity, and runtime, not only whether a user has access to an AI tool [src-170].
  • OpenAI's internal usage should be treated as directional: the paper says OpenAI is unusually favorable because employees have strong AI familiarity, buy-in, cheap marginal usage, and frequent knowledge sharing [src-170].

Related entities

Related concepts

Source references

  • [src-169] OpenAI – "How agents are transforming work" (2026-06-25)
  • [src-170] Drew Johnston, David Holtz, Alex Martin Richmond, Christopher Ong, Prasanna Tambe, Aaron Chatterji / OpenAI – "The shift to agentic AI: Evidence from Codex" (2026-06-25)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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