VfL Wolfsburg turned ChatGPT into an operational capability, not an isolated project. How did a traditional football club start using AI in daily tasks without creating technical dependence? You might expect a long tech overhaul — but they did it with practice, human names for assistants, and a focus on repetitive tasks.
What Wolfsburg did
The club applied ChatGPT Enterprise as the backbone to democratize AI among employees. Today they report more than 50 personalized GPTs in daily use and nearly 100 across their ecosystem, with plans to give access to around 350 colleagues.
This wasn't experimentation for its own sake. They aimed to save time, cut external costs, and standardize quality without inflating the payroll. The result: six-figure annual savings and much faster processes like writing, translating, and generating documents.
How they implemented it and why it worked
First they stopped talking in the abstract and started working with the people who do the work every day. Instead of long strategies, they ran workshops, hands-on tests, and use cases led by each department.
Some clear principles:
- Start with repetitive tasks and existing templates.
- Build assistants with human names to lower psychological resistance.
- Train "GPT Champions" or "GPTlers" inside areas to ease local adoption.
"ChatGPT only creates sustainable advantages if it’s understandable and usable for everyone, not just for experts," says Claudio Demmer, Business Innovation Lead.
Choosing ChatGPT Enterprise answered concrete needs: output quality, security and governance (including options for EU servers and a policy not to use customer data to train models), fast time-to-value, and ease for non-technical users.
Concrete results
- More than 50 assistants in daily use and nearly 100 on the internal platform.
- Scaled access to 350 employees as the immediate goal.
- Six-figure annual savings by reducing outsourced repetitive work.
- Wide adoption: from communications and marketing to HR, operations, and former players.
Adoption took off when the approach was practical: find a bottleneck, turn it into a GPT, and open it to the team.
Examples that help understand it
- Turf Disease GPT (Operations): you upload a photo of the pitch and get likely causes, checks, and a structured treatment plan. That way the know-how isn't stuck in one person.
- Football School Invoicing GPT (Administration): turns structured information into ready, brand-formatted invoices.
- "Hannah" (GPT builder for HR): asks seven standard questions and generates safe prompts so non-technical teams can create their own GPTs.
- ESG Check GPT (ESG): produces structured assessments with goals, measures, and a simple traffic-light indicator.
These examples show something important: AI doesn't replace human responsibility; it speeds it up and standardizes it.
Culture and change: the hardest and also the most valuable
The main challenge wasn't the technology, but change management in a diverse organization. For Wolfsburg, governance became an enabler. Making it clear that AI supports work and responsibility remains human helped build trust.
Who jumped in surprised them: colleagues who aren't digital natives, former players, and administrative teams began requesting their own GPTs. One clear anecdote: a former player left a workshop excited because he could create an assistant for the stories he tells the kids he coaches.
What's next for Wolfsburg?
Scale access to ChatGPT Enterprise across the whole club, keep training "GPTlers," and move forward with external fan- and member-oriented applications (personalization, internationalization, interactive formats) once governance is mature.
The challenge is to keep creative speed while setting a safe, consistent usage standard. If they nail that, AI shifts from a one-off tool to an organizational capability.
Final reflection
This isn't magic or a shortcut: it's process and cultural change. Wolfsburg shows that with a practical focus, clear governance, and localized training, AI can transform everyday tasks and free up time for what really matters: strategy and the game.
Original source
https://openai.com/index/vfl-wolfsburg
Summary: VfL Wolfsburg turned ChatGPT Enterprise into an organizational capability with more than 50 assistants in daily use, nearly 100 in their ecosystem, and six-figure annual savings. The key was applying AI to repetitive tasks, training internal "GPTlers," and prioritizing governance and usability.