Does Your AI Fall Under the EU AI Act and Do You Know What That Means?

The Problem

The EU AI Act is now in force. High-risk AI systems face conformity assessments, mandatory human oversight, and ongoing monitoring requirements. Prohibited systems must be stopped entirely. And with penalties reaching €15 million or 3% of global annual turnover, "we didn't know" is not a viable compliance strategy.

The challenge most practitioners face isn't awareness — it's classification. Before you can build a compliance program, you need to know which risk tier your AI systems fall into and what obligations that triggers.

That's what this guide is for.

Who Is This For

This guide is built for organizational leaders and practitioners who are accountable for AI adoption, compliance, or risk — and need to get up to speed on EU AI Act requirements without a law degree.

If you're a PMO leader, compliance or risk professional, AI Center of Excellence member, operations or product manager, or internal auditor, this guide gives you a clear, actionable starting point.

What You'll Get

The EU AI Act Risk Classification Quick Reference Guide gives you a practitioner-ready reference covering everything you need to classify your AI systems and understand your obligations — without wading through 150 pages of regulatory text.

Inside the 9-page guide:

The Four Risk Levels — Prohibited, High-Risk, Limited-Risk, and Minimal-Risk, with clear definitions and what each requires from your organization.

Prohibited AI Practices (Article 5) — The specific AI uses that are banned outright under the EU AI Act, including subliminal manipulation, social scoring, and real-time facial recognition. If your organization is running any of these, no amount of compliance work will fix it — you must stop.

All 8 High-Risk Categories (Annex III) — Biometrics, critical infrastructure, education, employment, essential services, law enforcement, migration/asylum, and justice — with real-world examples in each category and the key question to ask about your own systems.

Limited-Risk Transparency Requirements — What disclosure is required for chatbots, emotion recognition, biometric categorization, and synthetic media, and when the obligation applies.

A Quick Decision Tree — A visual flowchart to walk any AI system from Start to risk classification in four decision points.

Common Scenarios with Quick Answers — 11 real-world AI use cases (resume screening, loan approval, customer service chatbots, product recommendations, and more) with their official risk classifications.

Key Reminders That Save You From Costly Mistakes — Including the "significantly influences" trigger, why your vendor's classification may not be your classification, and how to handle one AI system with multiple use cases.