ChatGPT AI apps are coming to Germany – what companies should clarify strategically now

With the introduction of ChatGPT AI apps in Europe—and thus also in Germany—generative AI is reaching a new level in the corporate context. Whereas previously the focus was primarily on experimentation, testing, or selective automation, the focus is now shifting noticeably from isolated AI applications to integrated, workflow-oriented application scenarios.

For companies, the question is no longer whether AI is relevant, but how it can be used sensibly and responsibly.

What exactly are ChatGPT AI apps?

ChatGPT AI apps enable external applications, data sources, and systems to be integrated directly into AI-supported workflows. Instead of using AI solely as a text generator or research aid, it becomes a kind of intelligent interface between humans, data, and software.

Examples:

• Querying CRM, ERP, or project management data using natural language
• Automated evaluations, summaries, or decision-making bases
• Interaction with specialist systems without classic user interfaces
  
  

This brings AI closer to operational processes—and finally leaves the playground of individual experiments behind.

Why this topic is now becoming strategically relevant

• Specialist departments see concrete potential for efficiency gains.
• IT departments must evaluate security, integration, and governance.
• Management teams are faced with the question of competitive advantages and risks.

The real challenge: decisions, not technology

1. “We have to be quick.”
   Speed is not an end in itself. A false start often costs more than a later, but cleaner, entry.
2. “This is an IT issue.”
   AI apps affect processes, roles, responsibilities, and decision-making logic—not just systems.
3. “Let's just test it out.”
   Tests without clear questions generate insights, but rarely provide guidance.

First Mover or Fast Follower?

One of the key questions for many companies right now is: jump in early or wait and see?

Both strategies can make sense—if they are chosen deliberately.

First movers benefit from learning curves, an image of innovation, and early efficiency gains, but they also bear higher risks.

Fast followers can learn from the experiences of others, but they must accept that competitive advantages may already have been distributed.

The decisive factor is not the category, but clarity about goals, framework conditions, and risks.

What companies should do now in concrete terms

Instead of rushing into implementation, we recommend three steps:

Assessing relevance
Where could AI apps create real added value—and where not?

Evaluating risks
Data protection, compliance, dependencies, organizational implications.

Defining a clear strategy
Test fields, responsibilities, decision-making logic, and next steps.

This is precisely where many organizations fail, not because of a lack of will, but because of a lack of structure.

What exactly do ChatGPT AI apps mean for your company?

Let's work together to identify opportunities, risks, and sensible next steps
in a structured and non-binding manner.

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