TABLE OF CONTENTS:

1. How To Use This Document 4

Structure and Content Overview 4

Guidance for Readers 5

2. Background 6

What Are Large Language Models? 6

How Do Large Language Models Work? 6

Emerging LLM Technologies: The Rise of Agentic AI 12

Common Uses of LLM Systems 15

Performance Measures for LLMs 18

3. Data Flow and Associated Privacy Risks in LLM Systems 24

The Importance of the AI Lifecycle in Privacy Risk Management 24

Data Flow and Privacy Risks per LLM Service Model 26

Roles in LLMs Service Models According to the AI Act and the GDPR 43

4. Data Protection and Privacy Risk Assessment: Risk Identification 48

Criteria to Consider when Identifying Risks 48

Examples of Privacy Risks in LLM Systems 51

5. Data Protection and Privacy Risk Assessment: Risk Estimation & Evaluation 57

From Risk Identification to Risk Evaluation 57

Criteria to Establish the Probability of Risks in LLM Systems 58

Criteria to Establish the Severity of Risks in LLM Systems 60

Risk Evaluation: Classification of Risks 65

6. Data Protection and Privacy Risk Control 66

Risk Treatment Criteria 66

Example of Mitigation Measures Related to Risks of LLM Systems 67

7. Residual Risk Evaluation 74

Identify, Analyze and Evaluate Residual Risk 74

8. Review & Monitor 75

Risk Management Process Review 75

Continuous Monitoring 75

9. Examples of LLM Systems’ Risk Assessments 80

First Use Case: A Virtual Assistant (Chatbot) for Customer Queries 80

Second Use Case: LLM System for Monitoring and Supporting Student Progress 91

Third Use Case: AI Assistant for Travel and Schedule Management 94

10. Reference to Tools, Methodologies, Benchmarks and Guidance 97

Evaluation Metrics for LLMs 97

Other Tools and Guidance 99