AI technology has reached every corner of the organization. From operational processes to strategic decision-making, automation and intelligence support more and more parts of daily work.
But much of this technology comes from the United States. Major AI systems and platforms are developed, hosted, and operated by American tech giants such as Microsoft, Google, OpenAI, Meta, and Amazon.
For European companies, this raises important questions.
- What about data security and privacy?
- What legislation do you need to comply with?
- How do you maintain control over what AI does on behalf of your organization?
In this article, we explain what to pay attention to, what the risks are, and what your organization can do right now.
AI Still Comes from the United States
Most AI tools in use today are developed in the US. ChatGPT (OpenAI), Gemini (Google), Copilot (Microsoft), and Claude (Anthropic) are all American products. They are powerful, accessible, and often user-friendly. But there is a downside.
Using American technology also means
- being subject to US legal frameworks such as the CLOUD Act.
- It means operating under American norms and values, such as those concerning privacy, profit orientation, or bias.
- It also means depending on American market dominance, which can create reliance for European companies.
Even if an AI model runs on a European server, US law often still applies if the parent company is based in the US. This creates legal friction, especially with European regulations like the GDPR.
The main risks at a glance
If your organization uses AI developed in the United States, these five risks are the most important to consider.
1. Privacy and Data Access
The US government can access data from American companies under certain conditions, even when the data is physically stored in Europe.
Result: This means you may unknowingly violate privacy regulations such as the GDPR, which can lead to reputational or financial harm.
2. Limited Transparency
Many AI models are black boxes. They generate results, but it is unclear how those results are produced.
Result: This makes it difficult to explain decisions to clients or regulators, even though the EU AI Act will require exactly that level of transparency.
3. Dependency on Large Platforms
AI tools are often delivered as a service through platforms like Azure, AWS, or Google Cloud.
Result: When the provider changes terms, pricing, or access, your organization has limited influence.
4. Ethical Tensions
AI models are trained on data sets that do not represent European contexts very well. Much of this training data comes from English-language sources and reflects American social, cultural, and legal standards. As a result, AI systems may not align with the diversity of languages, customs, and laws in Europe. Think of how AI deals with privacy, cultural sensitivities, or regional terminology.
This can cause AI models to produce biased answers or overlook nuances that are important to European users. This increases the risk of bias, discrimination, or unequal treatment, especially in sectors where AI directly impacts people, such as HR, marketing, or public services.
5. Limited Ownership and Control
Many companies build applications on top of American AI models but do not have access to the source code or training data.
Result: This limits your control over what the system knows, forgets, or learns.
What Can You Do as an Organization?
You do not need to avoid AI, but you must make informed choices. Here are six steps you can take today.
1. Map your AI landscape
Which AI tools does your organization use? Where do they come from? What data do they rely on? Who is responsible for AI use within your organization? Make this visible so you can assess risks.
2. Choose vendors carefully
Don’t focus only on functionality. Also consider:
- Legal jurisdiction of the vendor
- Data processing and storage
- Transparency and explainability
- Your rights to your own data
3. Assess AI for ethics and inclusion
Ask critical questions like:
- Is the system fair and transparent for everyone?
- Does it actively address bias and inequality?
- s there room for human objection or correction?
Work with an ethical framework or AI principles that reflect your organization’s values.
4. Ensure legal compliance
The GDPR always applies when processing personal data.
The EU AI Act is coming soon, especially relevant if you use AI in sensitive areas like HR, education, healthcare, or government.
Involve your legal and compliance teams from the start.
5. Build internal knowledge
AI isn’t just an IT matter. Involve HR, communications, legal and policy as well. Train teams to use AI responsibly and recognize risks.
6. Be transparent with customers and users
Are you using AI? Say so. Explain how you use it, what the limitations are, and how people can ask questions or raise concerns.
In conclusion: Technology is never neutral
AI is powerful, fast, and full of potential. But it is not a neutral technology. How AI works and who benefits from it is largely determined by who develops it and why.
As a European organization, you may not always have a choice in whether you use American AI, but you can choose how to use it. By making conscious procurement decisions, reducing risks, complying with laws, and prioritizing transparency, you build a resilient and trustworthy organization.
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