Codex正成为每个人的生产力工具

OpenAI 今日发布新报告⁠(在新窗口中打开)《知识工作的下一个时代》，展示了 Codex 已不再仅仅是编码工具。它正日益帮助各行业从业者自动化常规工作、提升效率，并消除现代知识工作中的瓶颈。

Codex 目前拥有超过 500 万周活跃用户，自 2 月桌面应用上线以来增长超过 6 倍。虽然开发者仍是最大用户群体，但知识工作者现已占用户总数的约 20%，且增速是前者的三倍以上。

数据表明更广泛的变革正在发生。知识工作者主要使用 Codex 创建报告、电子表格、演示文稿、合同及其他工作成果。他们也越来越频繁地将其用于研究、数据分析、工作流自动化，以及构建此前需要工程支持才能完成的轻量级工具。

增长最快的知识工作者任务包括数据分析、研究和知识成果创建。与此同时，用户正越来越多地并行运行多个 Codex 任务，使其能够同时进行数据调研、材料起草和工作流自动化。这种效率提升可能重塑 AI 对工作的长期影响：Codex 能帮助人们承担更具雄心的项目，从而拓展其职责范围，并可能加速职业发展。

各行业的模式相似：人们正利用 Codex 减少现代工作中的摩擦。它帮助用户查找分散在多个系统中的信息、协调跨工具和团队的工作、产出高质量交付物，并推动项目完成审核与审批流程。

OpenAI today released a new report⁠(opens in a new window), The Next Era of Knowledge Work, showing how Codex is no longer just a coding tool. Increasingly, it’s helping people across professions automate routine work, move faster, and eliminate the bottlenecks of modern knowledge work.

Codex now has more than 5 million weekly active users, up more than 6x since the launch of the desktop app in February. While developers remain the largest user group, knowledge workers now represent about 20 percent of users and are growing more than three times as fast.

The data suggests a broader shift is underway. Knowledge workers primarily use Codex to create reports, spreadsheets, presentations, contracts, and other work products. They are also increasingly using it for research, data analysis, workflow automation, and building lightweight tools that previously required engineering support.

The fastest-growing knowledge-worker tasks are data analysis, research, and knowledge artifact creation. At the same time, users are increasingly running multiple Codex tasks in parallel, allowing them to investigate data, draft materials, and automate workflows simultaneously. This kind of increased velocity could reshape AI’s long-term impact on work: Codex can help people take on more ambitious projects, leading to greater scope of their roles, and potentially accelerate career advancement.

Across industries, the pattern is similar: people are using Codex to reduce the friction of modern work. It helps them find information buried across systems, coordinate work across tools and teams, produce high-quality deliverables, and move projects through review and approval processes.