STADLER AI Implementation and Productivity Gains

STADLER, a global leader in automated waste sorting plants, has integrated OpenAI's ChatGPT to transform knowledge work across its 650-employee organization. By treating AI as a core productivity layer rather than a standalone tool, the company has reduced the time spent on summarizing, translating, and drafting by 30-40%.

Company-Wide AI Integration Strategy

STADLER's approach to AI adoption was driven by the need to reduce friction in turning raw knowledge into usable output. Under the leadership of Co-CEO Julia Stadler, the company adopted ChatGPT based on its output quality, speed, and immediate usability compared to alternatives.

The implementation followed a hybrid model of bottom-up experimentation and top-down support, providing employees with company-wide access, training, and guardrails. This has resulted in over 85% daily active usage, with employees engaging with the tool multiple times per day.

Functional Use Cases and Custom GPTs

ChatGPT is now embedded across nearly every business function at STADLER, with the company creating more than 125 custom GPTs to standardize workflows. Key applications include:

• Engineering and Data Teams: Used for performance evaluation, code support, and analysis.
• Project and Management Teams: Utilizing custom GPTs to structure processes and improve documentation.
• Marketing Teams: Translating complex technical knowledge into global communications.
• General Operations: Drafting, research, summarizing, and structured thinking across all teams.

Measurable Productivity Impacts

STADLER reports significant acceleration in the output generation process, moving from half-day timelines for first drafts to 20-minute completions. The measurable outcomes include:

• Time Savings: 30-40% reduction in time spent on common knowledge tasks such as documentation and summarizing.
• Drafting Speed: An average 2.5x increase in speed to first draft, with high-volume use cases like social media seeing up to 6x acceleration.
• Operational Efficiency: Faster decision-making through quicker access to structured insights and improved clarity and consistency in outputs.

"ChatGPT isn’t just a writing tool—it’s a thinking partner that helps structure ideas and accelerate how we work." — Dr. Bastian Küppers, Head of Process Engineering

Future Evolution: Transition to AI Agents

Following the success of the assistant-based model, STADLER is moving toward an execution layer. The next phase of their digital transformation involves integrating AI agents into core workflows. These agents will be designed to gather information, generate outputs, validate them against established standards, and and route work for approval.