From assistance to execution: How enterprises put AI to work

Organizations are expanding both where they use AI and what they ask it to do. Enterprise AI is moving from assistance to execution, yet not all firms are making that transition at the same pace. Frontier firms—those in the top 10% of AI usage each month—now generate 8.3× as many output tokens per active user as typical firms. The measure is a proxy for depth of use, and the widening gap appears alongside greater adoption of capabilities that connect agents to company context, tools, and repeatable workflows.

Today we are publishing two complementary studies that examine this shift. Enterprise Signals leads with a practical view of agentic AI across OpenAI’s enterprise customer base, including what frontier firms are doing differently and where agentic work is spreading. The companion working paper, How Organizations Use AI: Evidence from ChatGPT⁠(opens in a new window), examines how adoption grows across companies, roles, and levels of seniority.

Together, the studies point to a practical enterprise agenda: connect agents to the context and tools needed to complete valuable work; establish clear permissions, review, and governance; and help employees turn effective individual workflows into shared ways of working.

These reports reveal five key insights on how organizations are putting AI to work:

Enterprises are shifting from asking to doing

Enterprise AI is moving from answering questions to carrying out work. Assistants help people think through work; agents help them complete it. Products like ChatGPT Work and Codex can use tools, create files, and produce work for review. Instead of asking AI how to prepare a presentation, for example, a worker can ask an agent to gather relevant information across sources and draft the presentation itself.