Certified EU AI Data Protection & Privacy Professional (AIData)

The Certified EU AI Data Protection & Privacy Professional (AIData) is an ECVC credential that validates the ability to interpret and apply EU data protection and privacy requirements in AI system contexts. It focuses on the GDPR, the EU AI Act, the ePrivacy Directive, official Commission AI Act guidance, and supervisory guidance on profiling and automated decision-making. Positioned as a privacy-specialist AI credential, it confirms competence in assessing whether AI systems process personal data lawfully, transparently, minimally, securely, and accountably under EU privacy rules. The scope covers legislation and guidance translated into practical AI privacy governance, including compliance, risk assessment, safeguards, lawful basis, transparency, security, accountability, and processor management.

Why this Certification

For Organisations

Translates AI privacy obligations into structured, practical, and auditable compliance operations.
Helps identify where AI systems process personal data and assess lawful bases for processing.
Supports review of training data and input data used by AI systems.
Strengthens management of profiling risks and supports DPIAs (Data Protection Impact Assessments).
Promotes privacy by design and privacy by default practices.
Helps maintain evidence of GDPR accountability.
Enables organisations to distinguish between AI governance obligations and AI data protection and privacy compliance obligations.
Supports compliance where AI systems involve personal data, biometric data, special category data, employee monitoring, customer scoring, behavioural advertising, automated decision-making, or international data transfers.
Improves collaboration between privacy, legal, compliance, AI governance, cybersecurity, HR, marketing, procurement, and data science teams.
Strengthens GDPR compliance and AI privacy governance.
Enhances vendor due diligence, documentation quality, and DPIA readiness.
Improves transparency practices and data subject rights handling.
Increases preparedness for engagement with supervisory authorities.
Reduces regulatory, operational, reputational, and fundamental-rights risks.
Helps address risks arising from opaque profiling, excessive data use, inaccurate outputs, weak safeguards, and unclear controller and processor responsibilities.

For Individuals

Shows verified knowledge of EU AI privacy and data protection.
Covers understanding of GDPR, EU AI Act, ePrivacy rules, and official guidance.
Builds ability to turn rules into practical privacy work (controls, documents, workflows).
Helps with DPIAs (risk assessments) and AI compliance tasks.
Useful across roles in privacy, legal, AI governance, cybersecurity, and compliance.
Improves communication with DPOs, legal teams, engineers, and AI vendors.
Supports real work like data use checks, transparency reviews, and risk assessments.
Helps manage AI privacy risks (profiling, biometric data, automated decisions, data transfers).
Strengthens career credibility in GDPR + AI compliance.

Learning Objectives

By the end of this certification, candidates will be able to:

Interpret the GDPR in AI system contexts, including principles of lawfulness, fairness, transparency, purpose limitation, data minimisation, accuracy, storage limitation, integrity, confidentiality, and accountability
Understand how the AI Act interacts with EU data protection, privacy, and confidentiality of communications rules
Apply the AI Act definition of an AI system when assessing whether AI-related privacy risks fall within AI lifecycle governance
Distinguish AI data protection and privacy compliance from broader AI ethics and general AI Act compliance
Identify personal data processing activities across AI system design, training, validation, deployment, monitoring, and use
Assess lawful bases for AI-related personal data processing, including consent, contract necessity, legal obligation, public interest, vital interests, and legitimate interests
Recognise when AI systems involve profiling, automated decision-making, or solely automated decisions with legal or similarly significant effects
Apply GDPR safeguards for profiling and automated decision-making, including transparency, data subject rights, meaningful human involvement, contestability, and appropriate safeguards
Identify and assess risks linked to inferred data, derived data, behavioural data, location data, biometric data, special category data, and vulnerable data subjects
Understand the privacy relevance of AI Act prohibited practices, including social scoring, certain profiling-based criminal risk assessment, untargeted facial image scraping, emotion recognition in workplace and education contexts, and biometric categorisation practices
Support privacy notices and transparency information for AI systems, including information about profiling, automated decision-making, logic involved, significance, and envisaged consequences where applicable
Operationalise data subject rights in AI contexts, including access, rectification, erasure, restriction, objection, and rights linked to automated decision-making
Conduct and document AI-related DPIA inputs, including risk identification, necessity and proportionality analysis, safeguards, residual risks, and accountability evidence
Embed privacy by design and by default into AI product development, procurement, testing, deployment, and monitoring
Assess data minimisation, purpose limitation, accuracy, retention, and security controls for AI datasets and AI outputs
Understand controller, joint controller, processor, provider, deployer, and vendor responsibilities in AI supply chains
Review data processing agreements and standard contractual clauses where AI vendors or AI infrastructure involve processors or international personal data transfers
Coordinate AI privacy governance with legal, security, compliance, product, procurement, HR, marketing, data science, and management teams
Maintain auditable AI privacy documentation, including records of processing, DPIAs, vendor evidence, transfer safeguards, transparency materials, and internal decision records
Advise stakeholders on practical AI privacy risks without treating the certification as a broad AI ethics or general AI Act compliance qualification.

Target Audience

This certification is ideal for:

Current or aspiring Data Protection Officers working with AI.
Privacy managers, privacy analysts, and data protection professionals.
AI governance and compliance professionals.
Legal counsel and regulatory affairs professionals.
Governance, risk, compliance, audit, and internal control professionals.
Information security and cybersecurity professionals.
Product managers, product owners, and engineering leads building or deploying AI-enabled products
Data scientists, machine learning teams, and AI project teams.
HR, recruitment, and People Operations teams.
Marketing, CRM, advertising, and analytics teams.
Healthcare, education, finance, insurance, public-sector, and security professionals.
Procurement and vendor management teams.
Consultants supporting GDPR compliance, AI privacy readiness, DPIAs, vendor reviews, or AI system assessments
Public-sector officers and policy professionals working with AI systems, privacy impact, automated decision-making, or digital governance
Business leaders and decision-makers responsible for trustworthy AI deployment, privacy governance, regulatory assurance, and data protection accountability.

Exam Format

This is a closed book online proctored exam powered by ECVC examination platform:

Multiple choice questions
50 questions per exam
60 minutes duration
At least 32 questions need to be answered correctly to pass the exam
One mark awarded for every correct answer
No negative maring for wrong answers
Difficulty level: Medium
EQF Level: 5

Download Exam Platform Handbook

Study Material

Core:

Regulation (EU) 2024/1689 – Laying down harmonised rules on Artificial Intelligence (Artificial Intelligence Act)
Regulation (EU) 2016/679 (GDPR)
Guidelines on the definition of an artificial intelligence system established by Regulation (EU) 2024/1689 (AI Act)
Commission Guidelines on prohibited artificial intelligence practices established by Regulation (EU) 2024/1689 (AI Act)
ePrivacy Directive — EUR-Lex consolidated text
Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679
Commission Implementing Decision (EU) 2021/914 — SCCs for international transfers
Commission Implementing Decision (EU) 2021/915 — SCCs between controllers and processors

Reading materials can be found here.

Candidates who wish to review additional Commission materials on EU Standard Contractual Clauses, international data transfers, and transfer safeguards may access the supplementary reference materials here. These resources are provided for contextual understanding and further reading. The examination primarily focuses on the certification’s core study materials.

Download Handbook

Prerequisites

There are no formal prerequisites. However, it is helpful to have:

Basic understanding of the GDPR structure and key terms such as personal data, controller, processor, data subject, lawful basis, consent, legitimate interests, DPIA, and data subject rights.
Familiarity with AI-related concepts such as AI system, model, training data, input data, output, inference, profiling, automated decision-making, biometric data, and AI lifecycle.
Introductory awareness of the EU AI Act and its relationship with data protection, privacy, transparency, fundamental rights, and risk-based governance.
Familiarity with how organisations use AI tools in HR, marketing, analytics, finance, education, healthcare, public services, security, or customer operations.
Comfort reading EU legal texts, official Commission guidance, and supervisory guidance, and translating them into practical requirements for stakeholders.
Introductory knowledge of information security controls such as access control, encryption, logging, monitoring, vendor security, and incident response.
Awareness of international data transfer concepts, including third-country transfers, SCCs, processors, sub-processors, and transfer safeguards.
Experience in a related field is helpful but not required, for example privacy, compliance, legal, cybersecurity, risk, audit, product, AI governance, data science, procurement, HR, marketing, or public policy.
Suitable for both technical and non-technical professionals involved in AI data protection, AI privacy compliance, GDPR implementation, AI system governance, DPIAs, or EU digital regulation.