Overview

This course equips professionals with the knowledge and tools to identify, assess, and mitigate AI-related risks within modern organisations. It explores the principles of AI governance, compliance, and ethics through globally recognised frameworks such as the NIST AI Risk Management Framework and the EU AI Act. Learners will gain hands-on experience applying these frameworks to real-world scenarios involving bias, security vulnerabilities, and transparency challenges. By the end of the course, participants will understand how to embed AI risk management within organisational strategy to ensure responsible, compliant, and ethical AI adoption.

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Prerequisites

Participants should have:

  • A foundational understanding of artificial intelligence concepts and data governance principles
  • Basic knowledge of organisational risk management or information security practices
  • Familiarity with compliance and governance structures within a business environment

Target audience

This course is designed for:

  • Risk, compliance, and governance professionals managing AI-related initiatives
  • IT and security specialists responsible for evaluating AI systems and controls
  • Data scientists, AI developers, and engineers integrating responsible AI practices
  • Consultants advising on AI risk management and mitigation strategies
  • Legal, ethical, and compliance advisors specialising in AI regulations
  • Business leaders and decision-makers responsible for strategic AI adoption

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Learning Objectives

By the end of this course, learners will be able to:

  • Explain the key concepts and principles of AI risk management and governance
  • Apply frameworks such as the NIST AI Risk Management Framework and the EU AI Act to evaluate compliance and ethical considerations
  • Identify and assess AI risks, including bias, data security, transparency, and accountability concerns
  • Develop and implement AI risk mitigation and incident response strategies
  • Integrate AI risk management into wider business and compliance frameworks
  • Analyse real-world case studies to identify lessons learned and best practices for AI risk control
  • Promote responsible AI use across the organisation through governance and continual improvement
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Course Outline

Introduction to AI risk management

  • Understanding AI’s opportunities and challenges in modern organisations
  • Key terms, definitions, and risk management concepts
  • Overview of global AI risk management standards and regulations

AI risk identification, assessment, and measurement

  • Techniques for identifying and classifying AI-related risks
  • Quantitative and qualitative methods for risk assessment
  • Assessing AI model reliability, data integrity, and ethical exposure

AI risk mitigation, governance, and incident response

  • Designing mitigation strategies aligned with compliance frameworks
  • Developing governance structures for ethical AI deployment
  • Planning incident response and escalation procedures for AI failures or bias events

AI risk monitoring and continual improvement

  • Establishing metrics and KPIs for AI risk performance
  • Continuous evaluation of AI systems through audits and impact assessments
  • Integrating lessons learned into organisational governance frameworks

AI risk management in business strategy

  • Linking AI risk management with strategic planning and enterprise risk frameworks
  • Ensuring accountability and ethical oversight in AI operations
  • Building a culture of responsible and transparent AI innovation

Exams and assessments

Participants will complete a formal certification exam administered by PECB. Certification fees and the exam voucher are included in the course price. Candidates who do not pass on the first attempt may retake the exam once for free within 12 months of the initial attempt. Knowledge checks, exercises, and quizzes are provided throughout the course to reinforce learning and readiness for the certification exam.

Hands-on learning

This course includes:

  • Practical exercises based on real-world AI risk scenarios
  • Interactive group discussions and case-based simulations
  • Workshops on developing and applying AI risk management frameworks
  • Guidance from experienced instructors and access to over 450 pages of supporting materials

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QA is a PECB Authorized Platinum Partner.

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Dates & Locations

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Need to know

Frequently asked questions

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Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.

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How do QA’s online courses work?

QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course.

Once you have purchased the Online course and have completed your registration, you will receive the necessary details to enable you to immediately access it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.

When will I receive my joining instructions?

Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.

When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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