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Keep shoppingAI Risk Management for Professionals and Auditors
Role Play
227 students
AI Risk Management for Professionals and Auditors
Implement AI risk frameworks, governance controls, and audit practices across enterprise AI systems.
Created byFortivance Academy
Last updated 3/2026
English
What you'll learn
- Understand key AI risk concepts, including technical, ethical, and compliance-related risks.
- Apply global AI risk management frameworks like NIST AI RMF and ISO 42001.
- Conduct AI Impact Assessments to identify and mitigate potential harms.
- Evaluate AI systems for bias, fairness, explainability, and transparency.
- Design and implement a comprehensive AI risk governance and monitoring program.
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Course content
12 sections • 56 lectures • 8h 54m total length
Requirements
- No prior experience with AI risk management is required.
- A basic understanding of AI concepts and technologies is helpful but not mandatory.
Description
This course provides a comprehensive overview of AI Risk Management, covering essential principles, frameworks, and practical tools to identify, assess, and mitigate risks associated with Artificial Intelligence systems. Whether you're implementing AI within your organization or auditing its use, this course will equip you with actionable knowledge to manage AI responsibly and compliantly.
The course explores the following key topics:
Key AI Risk Concepts and Definitions, helping learners understand critical terminology and types of risks.
AI Governance Principles and Lifecycle, detailing responsible AI development from design to decommissioning.
AI Risk Identification and Classification, focusing on technical, ethical, legal, and operational risks.
Frameworks and Standards, including NIST AI RMF, ISO 42001, OECD AI Principles, and other global guidelines.
Bias, Fairness, and Explainability, exploring how to detect, measure, and mitigate algorithmic bias.
AI Impact Assessments (AIA), enabling learners to evaluate risks before and during AI deployments.
Monitoring, Auditing, and Continuous Risk Evaluation, ensuring AI systems remain compliant and trustworthy over time.
Additionally, the course provides a step-by-step guide to building an AI Risk Management Program, from setting governance structures to integrating responsible AI practices in operations.
By the end of the course, learners will be able to:
Understand the foundational concepts and terminology of AI Risk Management.
Apply key AI risk management frameworks such as NIST AI RMF and ISO 42001.
Identify and categorize AI risks across technical, ethical, and compliance dimensions.
Assess algorithmic bias, explainability, and fairness using practical tools.
Conduct AI Impact Assessments and align with regulatory expectations.
Monitor AI systems continuously for evolving risks and unintended outcomes.
Implement AI governance programs aligned with organizational goals and values.
Promote responsible and transparent AI use while maintaining stakeholder trust.
Through real-world case studies, practical templates, and expert-led guidance, this course empowers professionals to implement and sustain robust AI risk management practices that align with global standards and promote ethical AI adoption.
Who this course is for:
- Risk, compliance, and governance professionals looking to understand and manage AI risks.
- Data privacy officers, auditors, and legal professionals working with AI-enabled systems.
- AI project managers, product owners, and business leaders deploying AI in their organizations.