10 posts
The AI Act in practice: risk tiers, transparency, human oversight and DPIA. What a company deploying AI must do in 2026.
From August 2026, the AI Act is enforceable. What this means in practice: transparency, human oversight, DPIA, and how to design compliance from the first line of code—not after an incident.
AI Act high risk in 2026: which systems are subject to strict regulation, what obligations do HR tools, credit scoring, and customer assessment entail, and how to design compliance.
The AI Act classifies most clinical AI systems as high-risk. What this means in practice: explainability, human oversight, DPIA, and GDPR compliance in healthcare.
AI for content moderation automates violation detection at a scale humans can't handle. How to design a system with guardrails, human-gate, and AI Act compliance.
AI governance in a company is a set of policies, roles, and control mechanisms that enable responsible AI deployment, compliant with the AI Act and RODO. A practical guide.
Responsible AI innovation isn’t a values statement—it’s concrete design decisions: guardrails, human-in-the-loop, explainability, and AI Act compliance. How to implement it in your company.
The AI black box problem poses real legal and operational risks. How XAI, guardrails, and human oversight address it in production systems compliant with the AI Act.
Why human oversight isn't a brake on automation but its condition. Human-gate, explainability, and AI Act in one architecture.
Where algorithmic bias comes from, how to measure and mitigate it at every stage: from data through model to deployment. A practical guide from the 2026 perspective.
AI deployment in public administration in 2026: what a government office can delegate to AI, what it cannot, AI Act and GDPR transparency requirements for local government units. Practical guide.