From bias and privacy issues to security breaches, AI requires proper governance. If your organization leverages AI, it also needs to understand the latest best practices in AI risk management. Certifications and training programs equip teams with the latest knowledge on how to stay ahead of these risks.
With the EU AI Act, ISO/IEC 23894, ISO/IEC 42001, and NIST AI RMF shaping global standards, certified professionals are increasingly in demand to help organizations operationalize AI risk governance.
Whether you’re a compliance professional, data scientist, or executive who’s in charge of responsible AI adoption, these certifications, along with other AI security training and red team training courses, help you master frameworks like the NIST, EU AI Act, and ISO standards. Sign up for these AI risk management certifications and training programs to lead AI projects with confidence.
The NIST AI Risk Management Certification is designed for experts who want to lead AI programs. This course will train you in the NIST framework for responsible design and deployment. Not only will you learn how to monitor AI systems and apply AI threat detection based on the NIST framework, but you’ll also better understand overall risk management best practices.
This certification prepares professionals to implement AI governance programs aligned with the NIST AI RMF and ISO/IEC 42001 standards. Graduates often work in roles such as AI Compliance Officer, Governance Lead, or Responsible AI Program Manager.
Pricing: $4,495
Key lessons include:
The NIST certification is best for experts, but this free Coursera program on AI governance is perfect for non-technical leaders. It’s best suited for anyone who wants a foundational course in both AI and governance best practices. Learn what AI governance is, why it matters, and how to deploy it in your own organization.
This certification builds a foundational understanding of AI governance concepts, frameworks, and ethical considerations. Professionals completing this program often apply these principles when developing internal AI ethics policies or governance boards.
Pricing: Free
Key lessons include:
This training, provided by the Global Association of Risk Professionals, focuses on risk management for AI and machine learning. However, it takes anywhere from 100 to 130 hours to complete the training, so it’s best suited for experienced professionals. Successfully passing the exam at the end of this training will earn you the GARP RAI certification.
This certification equips risk managers and compliance professionals with advanced techniques to assess and mitigate AI risks within regulated industries, thereby enhancing their AI security posture. Professionals with the GARP RAI credential often work in AI model validation, model risk management, or compliance teams across financial institutions.
Pricing: $525+
Key lessons include:
The Professional Evaluation and Certification Board offers a full certification for anyone interested in leading AI risk management assessments. During this course, you’ll learn about NIST framework basics, the EU AI Act, and the MIT AI Risk Repository. You’ll participate in simulated scenarios and AI red teaming exercises to test your knowledge over the course of four days.
This certification prepares learners to lead AI risk assessments and align AI systems with international compliance frameworks. Certified professionals often serve as AI Governance Leads, Compliance Assessors, or Ethics Officers for organizations deploying high-impact AI systems.
Pricing: Contact for information
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IAPP is a non-profit specializing in AI governance and privacy. It offers the Certified AI Governance Professional (AIGP) certification, which demonstrates your ability to evaluate AI and ensure it operates in compliance with both laws and organizational guidelines.
Completion of this program demonstrates a professional’s ability to evaluate AI systems for fairness, privacy, and legal compliance across global frameworks. AIGP-certified professionals often work in roles related to AI governance, policy design, and privacy-by-design, ensuring that systems meet ISO/IEC 42001 and GDPR standards.
Pricing: $1,195+
Key lessons include:
The Risk Management Society offers this virtual workshop to teach attendees not only how to manage AI risks but also how to use this technology for detecting fraud. If you want to earn a certificate, this workshop is part of a four-part series. Successfully completing all four parts will earn you the RIMS Fundamentals of Risk Data, Analytics, and AI Certificate.
This certification equips professionals with practical techniques for applying AI in risk analytics, fraud prevention, and informed decision-making. Participants frequently apply these skills in enterprise risk, financial operations, and fraud detection teams.
Pricing: $400+
Key lessons include:
The table below summarizes the AI risk management certifications discussed in this article, including providers, focus areas, and pricing. ,
Compliance is always a concern with AI, but that’s just one piece of the puzzle. AI risk management also requires full transparency and resilient systems that can withstand the latest threats. As your company integrates AI into more systems, you need professionals who can mitigate AI risks.
Certifications build foundational expertise, but operationalizing AI risk management requires continuous monitoring and testing. Mindgard’s Offensive Security and AI Artifact Scanning solutions complement certified training by detecting vulnerabilities, ensuring compliance with frameworks such as NIST AI RMF and ISO/IEC 42001, and providing real-time assurance throughout the AI lifecycle. Book a Mindgard demo to see how you can turn AI risk governance into a measurable, auditable, and continuously monitored process.
Several frameworks can help guide AI risk management. Some of the most popular are the NIST AI Risk Management Framework (AI RMF), ISO/IEC 23894, and the EU AI Act.
Risks change frequently, but some of the biggest risks today are:
AI risk management is a cross-functional responsibility. Data scientists, compliance teams, cybersecurity experts, and executives all play a role. However, some companies also have AI governance boards or appoint Chief AI Ethics Officers to manage AI risks.
