- Experience in IT operations, risk management, cybersecurity, or compliance within government institutions
- Familiarity with organizational security practices and digital service delivery
- No prior technical expertise in AI systems required
Audience
- Government IT teams involved in digital services and systems integration
- Cybersecurity and risk professionals in public institutions
- Public sector audit, compliance, and governance personnel
Artificial Intelligence (AI) introduces new dimensions of operational risk, governance challenges, and cybersecurity exposure for government agencies and departments.
This instructor-led, live training (online or onsite) is aimed at public sector IT and risk professionals with limited prior experience in AI who wish to understand how to evaluate, monitor, and secure AI systems within a government or regulatory context.
By the end of this training, participants will be able to:
- Interpret key risk concepts related to AI systems, including bias, unpredictability, and model drift.
- Apply AI-specific governance and auditing frameworks such as NIST AI RMF and ISO/IEC 42001.
- Recognize cybersecurity threats targeting AI models and data pipelines.
- Establish cross-departmental risk management plans and policy alignment for AI deployment.
Format of the Course
- Interactive lecture and discussion of public sector use cases.
- AI governance framework exercises and policy mapping.
- Scenario-based threat modeling and risk evaluation.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Understanding AI-Specific Risk in Government Settings
- How AI risk differs from traditional IT and data risk
- Categories of AI risk: technical, operational, reputational, and ethical
- Public accountability and risk perception in government
AI Risk Management Frameworks
- NIST AI Risk Management Framework (AI RMF)
- ISO/IEC 42001:2023 — AI Management System Standard
- Other sector-specific and international guidance (e.g., OECD, UNESCO)
Security Threats to AI Systems
- Adversarial inputs, data poisoning, and model inversion
- Exposure of sensitive training data
- Supply chain and third-party model risks
Governance, Auditing, and Controls
- Human-in-the-loop and accountability mechanisms
- Auditable AI: documentation, versioning, and interpretability
- Internal controls, oversight roles, and compliance checkpoints
Risk Assessment and Mitigation Planning
- Building risk registers for AI use cases
- Collaborating with procurement, legal, and service design teams
- Conducting pre-deployment and post-deployment evaluations
Incident Response and Public-Sector Resilience
- Responding to AI-related incidents and breaches
- Communicating with stakeholders and the public
- Embedding AI risk practices in cybersecurity playbooks
Summary and Next Steps
United Arab Emirates - AI Risk Management and Security in the Public Sector
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