IICTI Certified Responsible AI Specialist

Holders demonstrate that they can apply and evaluate aI regulation and EU AI Act compliance engineering, aI management systems and governance frameworks, aI risk and impact assessment and fairness measurement and bias mitigation, plus 7 further areas, in realistic professional scenarios, as defined in the AQSCERT scheme for Responsible AI Specialist.

Who it is for: Professionals working, or preparing to work, in artificial intelligence roles.

1. 01AI regulation and EU AI Act compliance engineering9% of the exam

   • Evaluate AI systems against applicable regulation and design compliance pathways for each risk classification.
   • Scope: EU AI Act risk tiers, prohibited practices, high-risk obligations, GPAI and systemic-risk model duties, conformity assessment, harmonised standards, interplay with GDPR, DSA and sector rules, and global regimes (US state laws, China, UK).
2. 02AI management systems and governance frameworks6% of the exam

   • Design and lead an AI governance and management system that integrates with enterprise risk and compliance.
   • Scope: ISO/IEC 42001 AIMS, ISO/IEC 23894 risk management, NIST AI RMF 1.0 and Generative AI Profile, OECD AI Principles, governance structures, AI policies, roles and accountability, AI inventories.
3. 03AI risk and impact assessment11% of the exam

   • Lead AI impact assessments that identify, prioritise and treat risks to individuals, groups and society.
   • Scope: Algorithmic and fundamental rights impact assessments (FRIA), DPIAs for AI, ISO/IEC 42005, harm taxonomies, stakeholder and affected-community engagement, risk scoring and treatment decisions.
4. 04Fairness measurement and bias mitigation12% of the exam

   • Evaluate AI systems for unfair outcomes and justify fairness definitions and mitigations for the context of use.
   • Scope: Group and individual fairness metrics and their incompatibilities, intersectional analysis, dataset bias, pre-, in- and post-processing mitigation (Fairlearn, AIF360), non-discrimination law and context-specific fairness choices.
5. 05Transparency, explainability and documentation9% of the exam

   • Design transparency and documentation artefacts that meet regulatory duties and serve each stakeholder's needs.
   • Scope: Global and local explanation methods (SHAP, counterfactuals), explanation for different audiences, model cards, datasheets, system cards, AI Act technical documentation and transparency duties, content provenance (C2PA) and labelling.
6. 06Generative AI and foundation model risk evaluation9% of the exam

   • Design evaluation and red-teaming programmes that characterise and limit generative AI risks before and after deployment.
   • Scope: Hallucination and factuality, harmful content and misuse, red teaming and adversarial evaluation, benchmark and eval design, frontier capability thresholds, responsible scaling and acceptable-use policies.
7. 07Human oversight, agentic AI and accountability by design8% of the exam

   • Architect oversight and accountability mechanisms proportionate to system autonomy and impact.
   • Scope: Human-in-the-loop and on-the-loop designs, automation bias, contestability and redress, agent autonomy levels and permissioning, escalation and kill-switch controls, liability allocation across the AI value chain.
8. 08Privacy, data governance and security for AI systems13% of the exam

   • Evaluate data and security risks across the AI lifecycle and design proportionate safeguards.
   • Scope: Lawful basis and purpose limitation for training data, data provenance and copyright, privacy-enhancing technologies (differential privacy, federated learning), memorisation and inversion risks, AI security threats (MITRE ATLAS, OWASP LLM Top 10).
9. 09AI assurance, auditing and post-market monitoring11% of the exam

   • Lead AI assurance and audit activities that produce defensible evidence of ongoing trustworthy operation.
   • Scope: Internal and third-party AI audits, audit criteria and evidence, ISO/IEC 42006, continuous monitoring for drift and emerging harms, serious incident reporting, AI incident databases and corrective action.
10. 10Third-party AI procurement and value-chain risk6% of the exam

    • Evaluate third-party AI products and design procurement controls that allocate responsibility and manage residual risk.
    • Scope: Provider, deployer and importer roles, vendor due diligence, contractual AI clauses, foundation model and API dependency risk, open-source model licensing, documentation and information rights across the supply chain.
11. 11Leading responsible AI culture and organisational change6% of the exam

    • Lead organisational adoption of responsible AI practices with clear decision rights and measurable outcomes.
    • Scope: Ethics review boards, operating models, training and AI literacy obligations, incentive and metric design, ethical deliberation methods, stakeholder communication and handling of ethical escalations.

Question types

Single choice 100%

Delivery

Online (remote proctored), Test centre, On-site (corporate)

Retakes

Up to three attempts within any 12-month period. A 14-day waiting period applies after a first unsuccessful attempt and 30 days after a second. Each retake requires a new booking and fee. Retakes draw a different randomised form from the question bank.

Provisional cut score — psychometric validation is required before live delivery. Blueprint v1.0.

1. 1

   Register

   Create a free account and start the programme.

2. 2

   Practice

   Online practice test (coming soon).

3. 3

   Training

   Optional

   Online course or classroom — or skip it.

4. 4

   Certification

   Independent exam and certification decision.

Training is optional and does not by itself confer certification. Find a training partner