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PECB Lead AI Risk Manager

Assess AI risks in their organisational context and develop governance, risk treatment, monitoring and reporting practices.

Download the course brochurePECB Lead AI Risk Manager · PDF
30 hours / 5 days
3-hour PECB certification exam
Credential application subject to requirements
Artificial intelligence risk management

Bring AI risk management into organisational decision making

AI systems introduce risks involving bias, security and data privacy. Managing these risks supports responsible and reliable AI use.

PECB Lead AI Risk Manager training explores how to identify, assess, treat and monitor AI risks. Practical examples connect risk management with governance and ethical principles.

Audience

Who is it for?

Risk professionals identifying, assessing and managing AI-related risks
IT and information security professionals responsible for AI system security
Data scientists, developers and project managers working on AI initiatives
Specialists and consultants working in AI governance, ethics and regulatory compliance
Leaders overseeing AI adoption and strategic decision making
Program flow

Course content

01
Module 1 Introduction to AI Risk Management Fundamentals
  • Defining Artificial Intelligence and its transformative impact on organizations.
  • Understanding the unique characteristics of AI risks: bias, explainability, security, privacy.
  • Overview of AI risk management principles and the AI system lifecycle.
  • Introduction to key AI governance frameworks: NIST AI Risk Management Framework and EU AI Act.
  • Ethical considerations in AI development and deployment: fairness, accountability, transparency.
  • Exercise: Identifying AI risk categories across various industry applications.
02
Module 2 AI Risk Governance and Identification
  • Establishing the organizational context for AI risk management: scope and boundaries.
  • Developing an AI risk governance framework: roles, responsibilities, and policies.
  • Techniques for AI risk identification: brainstorming, checklists, scenario analysis.
  • Leveraging the MIT AI Risk Repository for comprehensive AI threat intelligence.
  • Identifying AI-specific vulnerabilities in data, algorithms, and deployment environments.
  • Exercise: Mapping AI risk ownership and accountability within an organizational chart.
03
Module 3 AI Risk Analysis, Evaluation, and Treatment
  • AI risk analysis methodologies: qualitative and quantitative assessment techniques.
  • Evaluating AI risk levels: likelihood, impact, and criticality scoring.
  • Developing AI risk acceptance criteria and risk appetite statements.
  • Formulating AI risk treatment options: avoidance, reduction, sharing, retention.
  • Designing AI security controls and data privacy measures for AI systems.
  • Implementing AI bias detection and mitigation strategies using automated tools.
  • Exercise: Developing an AI risk treatment plan for a high-priority AI risk scenario.
04
Module 4 AI Risk Monitoring, Reporting, and Optimization
  • Establishing AI risk monitoring programs: key performance indicators (KPIs) and risk indicators (KRIs).
  • Implementing continuous monitoring dashboards for AI system robustness and compliance.
  • AI risk reporting to stakeholders: executive summaries, compliance reports, audit findings.
  • Developing AI training and awareness programs for employees and leadership.
  • Optimizing AI risk management performance through lessons learned and corrective actions.
  • Integrating AI risk management with broader enterprise risk management (ERM) systems.
  • Exercise: Creating an AI risk monitoring plan with defined metrics and reporting frequencies.
05
Module 5 Certification Exam Preparation
  • Review of all competency domains: principles, governance, identification, evaluation, monitoring.
  • Deep dive into the PECB examination structure and question types.
  • Strategies for effective time management during the 3-hour exam.
  • Techniques for analysing scenarios and answering practice examination questions.
  • Practice with mock examination questions covering all course modules.
  • Clarification of challenging concepts and final Q&A session.
  • Exercise: Completing a full-length mock PECB Lead AI Risk Manager exam.
What you will gain

Build a structured approach to AI risk

Define risk ownership, plan appropriate controls and develop monitoring practices that support informed decisions and continual improvement.

01

Competency 1

Explain the characteristics of AI risks and their relationship with the system lifecycle.

02

Competency 2

Define organisational context, risk ownership and AI risk governance responsibilities.

03

Competency 3

Identify, analyse and evaluate AI risks using likelihood, impact and acceptance criteria.

04

Competency 4

Relate avoidance, reduction, sharing and retention options to appropriate controls.

05

Competency 5

Plan monitoring, reporting and awareness activities using performance and risk indicators.

06

Competency 6

Integrate AI risk management with enterprise risk management and continual improvement.

Selected PECB training

PECB Lead AI Risk Manager

A five-module programme spanning AI risk governance, analysis and treatment planning, monitoring, reporting and continual improvement.

PECB Lead AI Risk Manager
Official digital badge available once certification requirements are met.

About the training

PECB Lead AI Risk Manager training develops skills to identify, assess and manage AI risks. Practical examples address governance, security, privacy and ethical considerations.

The 30-hour, five-day programme includes five detailed modules and exam preparation. Key references include the NIST AI Risk Management Framework, the EU AI Act and the MIT AI Risk Repository.

Certificate

After passing the PECB exam, candidates may apply for a credential matching their experience and the applicable certification requirements. The Lead AI Risk Manager credential requires at least 5 years of professional experience, including 2 years in AI risk management, at least 300 hours of relevant activities and acceptance of the PECB Code of Ethics. Passing the exam alone does not confer this credential.

The BT Akademi Achievement Certificate is a separate award. According to the supplied course document, it is issued digitally with QR verification to participants who attend at least 80% of the training and successfully complete the assessments or projects required by the curriculum.

30 hours / 5 days 3-hour PECB certification exam Credential application subject to requirements
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