AI GLOSSARY

AI Compliance

AI compliance encompasses all legal and regulatory requirements for AI systems—from the EU AI Act and the GDPR to industry-specific rules. Anyone who uses AI productively must address compliance issues in a structured manner.

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4

Regulatory Frameworks
AI Act, GDPR, DORA, industry-specific

4

Key Areas
Risk, Data, Supervision, Documentation

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Roles
From AI Officer to Data Protection Officer

6

Best Practices
for Holistic Compliance

Why AI Compliance Is Strategically Important

AI compliance is more than just red tape—it builds trust with customers, regulators, and your team. And it protects against costly fines. By taking a structured approach early on, you can even turn compliance into a competitive advantage.
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Avoid Fines

The AI Act and GDPR carry the threat of fines in the millions for violations.

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Building Trust

Compliant AI builds trust with customers and regulators.

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Ensuring Market Access

Regulated industries require documentation—otherwise, no contract.

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Strengthening Internal Governance

Structured compliance improves AI systems overall.

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Competitive Advantage

Leverage early compliance as a unique selling point.

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Protecting Your Reputation

Compliance incidents are media disasters—but they are preventable.

What is AI compliance?

AI compliance refers to adherence to all legal, regulatory, and ethical requirements for AI systems used in business.

Key regulatory frameworks: EU AI Act (goes AI systems), GDPR (personal data), DORA (financial sector, digital resilience), Cyber Resilience Act (product safety), industry-specific rules (healthcare, legal system, finance).

Compliance encompasses several levels: legal analysis (what applies?), governance (roles, processes), technical implementation (security, fairness, transparency), documentation (evidence), and monitoring (ongoing).

For small and medium-sized enterprises, structured AI compliance is strategically important—it protects against penalties and lays the foundation for productive AI use in regulated sectors.

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Compliance Building Blocks in Detail

Eight building blocks are essential for robust AI compliance:

AI Registry

Centralized overview of all AI systems, including risk classifications and responsible parties.

Risk Management System

Systematic assessment and mitigation of AI risks throughout the lifecycle.

Data Protection Processes

AV Contracts, Legal Bases, and Data Subjects' Rights Regarding Personal Data.

Technical Documentation

Architecture, data, metrics — stored in an audit-ready format.

Transparency & Information

Users know that AI is involved—and just how much.

Human supervision

Human-in-the-loop and override capabilities are built in.

Monitoring & Reporting

Ongoing metrics on quality, fairness, and incidents.

Governance Structure

AI Officer, Committee, clear roles and responsibilities.

Best Practices for AI Compliance

These six principles help ensure successful AI compliance:

  • Adopt a cross-functional approach: IT, legal, compliance, and business units must work together.
  • Use a framework: ISO 42001 or the AI Act as a structural foundation.
  • GDPR Synergy: Expand existing data protection structures.
  • Automated monitoring: Display compliance metrics in dashboards.
  • Regular audits: A continuous process rather than a one-time action.
  • Training & Awareness: Ensure all AI users understand the requirements.
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Section 1

Legal Compliance

AI Act, GDPR, DORA. Mandatory—violations cost millions.

Must

Area 2

Governance

Internal rules, roles, and processes. Essential for stable operations.

Target

Area 3

Ethics & Values

Principles such as fairness, transparency, and a people-centered approach. Issues related to reputation and culture.

Should

Common Mistakes in AI Compliance

We frequently encounter these pitfalls:

  • Treatingcompliance as an IT issue: Incomplete without legal and business department input.
  • Focusing on just one set of regulations: Considering only the AI Act or only the GDPR—both are necessary, along with industry-specific requirements.
  • A One-Time Effort: Compliance is a process, not a project.
  • No AI Registry: Without an overview, there’s no way to manage compliance.
  • Unvetted vendors: Purchased AI without proof of compliance is a risk.

Compliance vs. Governance vs. Ethics

Three related concepts:

  • Compliance: Adherence to legal requirements. A must.
  • Governance: Control structures for AI use within the company. Should.
  • Ethics: Evaluation based on values and principles. Should.
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Katja Kammilla as the contact person for AI consulting

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Katja Kammilla
0203 3965080
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Frequently Asked Questions About AI Compliance

AI Compliance for Your Business

In a free initial consultation, we’ll assess your AI compliance maturity level and identify critical gaps—including a concrete implementation plan.

As an AI partner for small and medium-sized businesses, we’ll help you build your AI compliance in a structured way—with a framework, governance, and pragmatic implementation.

What We Offer

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