STADLER reshapes knowledge work at a 230-year-old company

从工业传承到数字化杠杆

家族企业 STADLER 拥有逾 230 年历史，专注为全球回收行业建造自动化垃圾分拣厂。公司在全球雇佣超过 650 名员工，在帮助各国推进可持续发展与循环经济目标方面发挥着重要作用。

在 Co-CEO Julia Stadler 的带领下，企业采取了前瞻性的现代化路径——将 AI 嵌入日常工作，作为提升生产力的核心层面。自 2023 年起， STADLER 推行一条明确原则：凡是在电脑上办公的员工，都应使用 AI 来提升速度、质量与协作效率。

“在许多团队里，人们把太多时间花在把原始知识变成可用产出上——总结、翻译、起草。我们知道必须有更好的方法。”—— Julia Stadler

把 AI 打造成公司级的生产力层

为消除上述摩擦， STADLER 选择采用 OpenAI 的 ChatGPT，理由是其输出质量、速度和即刻可用性。与其他方案比较后， ChatGPT 一贯能产出更具结构性、能联系上下文且实用的结果；更重要的是，它能立刻带来价值——团队从第一天起就能生成可用产出。

这一推行同时结合自下而上的试验与自上而下的支持。员工被鼓励探索使用场景，领导层则提供全公司访问权限、培训并设定清晰的使用边界。

如今， ChatGPT 几乎嵌入公司各职能部门：

• 工程与数据团队用于分析、代码支持与性能评估
• 项目与管理团队通过自定义 GPTs 规范流程、改进文档
• 市场团队将复杂技术知识转化为清晰的全球传播
• 所有团队用于起草、总结、调研与结构化思考

STADLER 已创建逾 125 个自定义 GPTs，在翻译与邮件工作流中采用尤为广泛。

“我们从需要半天才能拿到一个不错的初稿，进步到 20 分钟就能得到一个扎实的草稿，然后再去改进，” Julia Stadler 说。

“ ChatGPT 不只是写作工具——它是一个思考伙伴，能帮我们理清思路并加速工作进程。”—— Dr. Bastian Küppers，工艺工程负责人

（图注）工业回收厂内摆放着大型机器与压缩成捆的分拣塑料废料，工人在高台上监控作业。

从空白页到业绩影响

效果立竿见影且可量化。过去需要数小时的任务——起草文件、信息汇总、准备对外沟通——现在几分钟即可完成。员工不再从零开始，而是以结构化产出为起点，将精力放在润色、决策与更高价值的工作上。

主要成果包括：

• 在常见知识类任务（如总结与文档）上节省 30–40% 时间
• 首稿平均提速 2.5 倍，在社交媒体等高频场景中最高达 6 倍
• 日活跃使用率超过 85%，员工每天多次使用
• 更快的决策速度，源自更快获得结构化洞见
• 输出质量提高，表现为更清晰、一致与有结构
• 降低了启动与完成复杂任务的摩擦

“最有说服力的信号是人们回头使用的频率。当员工每天多次自发使用它时，你就知道它在创造真实价值。”—— Raphael Fricker，IT 负责人

除了效率提升， STADLER 的团队协作方式也发生了更广泛的转变。员工愈发用 ChatGPT 来厘清思路、探索想法并结构化复杂问题——从生产力工具逐步演变为认知工具。

下一步：从助手到执行层

STADLER 认为 AI 的角色将从辅助扩展到执行。下一阶段是将 AI 代理整合进核心工作流——这些系统能收集信息、生成产出、按标准校验并将工作分派审批。

对一家拥有两百多年历史的公司而言，这场转型已初见成效。通过把 AI 嵌入日常工作， STADLER 正以更高的速度、敏捷性与智能运行，释放其全球组织的新一轮生产力提升。

加入新工作时代

全球有超过一百万家企业已在与 OpenAI 合作中获得实质性成果。欲了解更多，请联系销售： OpenAI 。

From industrial legacy to digital leverage

STADLER is a family-owned company with more than 230 years of history, specializing in automated waste sorting plants for the global recycling industry. With over 650 employees operating worldwide, the company plays a critical role in helping countries advance their sustainability and circular economy goals.

Under the leadership of Co-CEO Julia Stadler, the company has taken a forward-looking approach to modernization—embedding AI into everyday work as a core productivity layer. Since 2023, STADLER has pursued a clear principle: every employee working on a computer should use AI to improve speed, quality, and collaboration.

“In many teams, people were spending too much time turning raw knowledge into usable output—summarizing, translating, drafting. We knew there had to be a better way.”

Turning AI into a company-wide productivity layer

STADLER adopted OpenAI's ChatGPT to remove this friction, selecting it for its output quality, speed, and immediate usability.

After evaluating alternatives, ChatGPT consistently delivered more structured, context-aware, and practically useful results. Just as importantly, it enabled immediate value—teams could start generating usable outputs from day one.

The rollout combined bottom-up experimentation with top-down support. Employees were encouraged to explore use cases, while leadership provided company-wide access, training, and clear guardrails.

Today, ChatGPT is embedded across nearly every function:

• Engineering & data teams use it for analysis, code support, and performance evaluation
• Project and management teams use custom GPTs to structure processes and improve documentation
• Marketing teams translate complex technical knowledge into clear global communication
• All teams use it for drafting, summarizing, research, and structured thinking

STADLER has created more than 125 custom GPTs, with particularly strong adoption in translation and email workflows.

"We moved from needing half a day to get a decent first version to having a solid draft in 20 minutes—and then improving it," says Julia Stadler.

“ChatGPT isn’t just a writing tool—it’s a thinking partner that helps structure ideas and accelerate how we work.”

From blank page to business impact

The impact has been immediate and measurable. Tasks that once took hours—drafting documents, summarizing information, preparing communication—are now completed in minutes.

Instead of starting from scratch, employees begin with structured outputs and focus on refinement, decision-making, and higher-value work.

Key outcomes include:

• 30-40% time savings on common knowledge tasks such as summarizing and documentation
• 2.5x faster time to first draft on average, with up to 6x acceleration in high-volume use cases like social media
• >85% daily active usage, with employees engaging multiple times per day
• Faster decision-making, driven by quicker access to structured insights
• Higher-quality outputs, with improved clarity, consistency, and structure
• Reduced friction, making complex tasks easier to start and complete

“The most meaningful signal is how often people come back to it. When employees use it multiple times a day without being asked, you know it’s delivering real value.”

Beyond efficiency gains, STADLER has seen a broader shift in how teams work. Employees increasingly use ChatGPT to clarify thinking, explore ideas, and structure complex problems. What started as a productivity tool became a cognitive one.

What comes next: from assistant to execution layer

STADLER now sees AI evolving beyond assistance into execution.

The next phase is integrating AI agents into core workflows—systems that can gather information, generate outputs, validate against standards, and route work for approval.

For a company with more than two centuries of history, the transformation is already clear. By embedding AI into everyday work, STADLER is operating with greater speed, agility, and intelligence—unlocking a new level of productivity across its global organization.

Join the new era of work

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