AI Governance & EU AI Act Compliance

AI Governance is not hype, but a responsibility

AI is being deployed ever more broadly across organizations: from customer service chatbots and HR screening to financial scoring models and generative tools for knowledge workers. At the same time, pressure is growing from legislation and clients to demonstrate that these AI systems are reliable, fair, and explainable. The EU AI Act, ISO 42001, NIST AI RMF, and sector-specific guidelines are no longer abstract frameworks — they require concrete processes around risk classification, data quality, human oversight, incident management, and model lifecycle. Without governance, every AI initiative becomes a risk issue one day.

We help organizations set up AI governance pragmatically. This starts with an AI inventory: which AI systems and generative tools are you already using today, who is responsible, what data goes in, and what decisions come out? Next, we classify systems according to the EU AI Act (prohibited, high-risk, limited-risk, minimal-risk) and determine which controls are appropriate per category. For high-risk systems, we build a governance framework with data quality requirements, bias testing, human oversight, transparency documentation, and incident response procedures.

Governance should not become a brake on innovation. That is why we work with a tiered approach: light governance for low-risk experiments, strict controls for production systems in regulated domains. We deliver templates, checklists, and a governance charter your teams can use themselves, and we train product owners and data scientists to recognize risks in their own working methods. For clients aiming for ISO 42001 certification, we use the governance framework as the basis for the AI Management System and guide you through the certification process.

Frequently asked questions about AI Governance