AI Risk Management and Security in the Public Sector Training Course

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at intermediate-level enterprise leaders who wish to understand how to govern and secure AI systems responsibly and in compliance with emerging global frameworks such as the EU AI Act, GDPR, ISO/IEC 42001, and the U.S. Executive Order on AI.

By the end of this training, participants will be able to:

• Understand the legal, ethical, and regulatory risks of using AI across departments.
• Interpret and apply major AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001).
• Establish security, auditing, and oversight policies for AI deployment in the enterprise.
• Develop procurement and usage guidelines for third-party and in-house AI systems.

AI policy and regulation is a rapidly evolving area that directly impacts how governments develop, adopt, and oversee artificial intelligence systems.

This instructor-led, live training (online or onsite) is aimed at public sector legal and compliance professionals with limited prior exposure to AI technologies who wish to understand regulatory developments, ethical frameworks, and policy considerations for responsible AI deployment.

By the end of this training, participants will be able to:

• Interpret key components of AI-related regulations such as the EU AI Act and GDPR.
• Assess national and international policy developments (Canada, U.S., OECD, etc.).
• Evaluate legal and ethical risks in AI procurement and use.
• Contribute to AI governance, oversight, and cross-agency alignment.

Format of the Course

• Interactive lecture and legal case analysis.
• Regulatory comparisons and policy mapping exercises.
• Scenario-based group discussion.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Artificial Intelligence (AI) is increasingly being used to improve the efficiency, accessibility, and responsiveness of public service delivery in areas such as taxation, healthcare, immigration, and social programs.

This instructor-led, live training (online or onsite) is aimed at public service delivery professionals with limited experience in AI who wish to explore real-world applications, automation strategies, and planning considerations for incorporating AI into front-line government services.

By the end of this training, participants will be able to:

• Identify areas in their department where AI can improve public service operations.
• Understand automation tools and AI-driven decision support systems.
• Explore use cases in forecasting, language access, and citizen assistance.
• Assess ethical, operational, and citizen trust factors in AI-enabled services.

Format of the Course

• Interactive lecture with real-life examples.
• Public sector use case walkthroughs and group discussion.
• Strategy planning exercises adapted to participants' departments.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI tools such as ChatGPT, Copilot, and Gemini are transforming administrative workflows by helping teams draft content, schedule meetings, respond to emails, and automate routine tasks.

This instructor-led, live training (online or onsite) is aimed at public sector administrative professionals with little to no prior experience in AI who wish to improve everyday productivity through the practical use of AI assistants and automation tools.

By the end of this training, participants will be able to:

• Understand how AI tools assist with common administrative tasks.
• Use ChatGPT, Copilot, and Gemini to generate emails, summaries, and documents.
• Integrate AI tools with calendars, task lists, and office software.
• Apply best practices for prompt writing and result interpretation.

Format of the Course

• Interactive lecture and guided demonstrations.
• Hands-on practice with real-world administrative tasks.
• Customizable exercises using the tools most relevant to participants' daily work.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.

By the end of this training, participants will be able to:

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
• Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at advanced-level government professionals and policy experts who wish to leverage DeepSeek for data-driven governance and policy innovation.

By the end of this training, participants will be able to:

• Utilize DeepSeek AI for policy analysis and strategic decision-making.
• Automate government reports and improve data transparency.
• Apply AI-driven insights for public sector innovation.
• Enhance citizen engagement through AI-powered solutions.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at intermediate-level public sector professionals who wish to use Gemini to generate high-quality content, assist with research, and improve productivity through more advanced AI interactions.

By the end of this training, participants will be able to:

• Craft more effective and tailored prompts for specific use cases.
• Generate original and creative content using Gemini.
• Summarize and compare complex information with precision.
• Use Gemini for brainstorming, planning, and organizing ideas efficiently.

Artificial Intelligence (AI) is transforming public sector operations, decision-making, and service delivery worldwide.

This instructor-led, live training (online or onsite) is aimed at public sector leaders with little to no prior background in AI who wish to understand the fundamentals of AI, assess its strategic relevance, and explore how it can be ethically and effectively adopted within government organizations.

By the end of this training, participants will be able to:

• Understand the key concepts and terminology in artificial intelligence.
• Evaluate AI’s opportunities and risks within public sector contexts.
• Explore the ethical and regulatory considerations relevant to AI use in government.
• Develop informed perspectives for AI-related policy, procurement, and strategy.

Format of the Course

• Interactive lecture and discussion.
• Real-world public sector case studies.
• Guided group reflection and policy exercises.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at beginner-level IT security, risk, and compliance professionals who wish to understand foundational AI security concepts, threat vectors, and global frameworks such as NIST AI RMF and ISO/IEC 42001.

By the end of this training, participants will be able to:

• Understand the unique security risks introduced by AI systems.
• Identify threat vectors such as adversarial attacks, data poisoning, and model inversion.
• Apply foundational governance models like the NIST AI Risk Management Framework.
• Align AI use with emerging standards, compliance guidelines, and ethical principles.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at advanced-level professionals who wish to implement and evaluate techniques such as federated learning, secure multiparty computation, homomorphic encryption, and differential privacy in real-world machine learning pipelines.

By the end of this training, participants will be able to:

• Understand and compare key privacy-preserving techniques in ML.
• Implement federated learning systems using open-source frameworks.
• Apply differential privacy for safe data sharing and model training.
• Use encryption and secure computation techniques to protect model inputs and outputs.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at advanced-level security professionals and ML specialists who wish to simulate attacks on AI systems, uncover vulnerabilities, and enhance the robustness of deployed AI models.

By the end of this training, participants will be able to:

• Simulate real-world threats to machine learning models.
• Generate adversarial examples to test model robustness.
• Assess the attack surface of AI APIs and pipelines.
• Design red teaming strategies for AI deployment environments.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at intermediate-level engineers and security professionals who wish to secure AI models deployed at the edge against threats such as tampering, data leakage, adversarial inputs, and physical attacks.

By the end of this training, participants will be able to:

• Identify and assess security risks in edge AI deployments.
• Apply tamper resistance and encrypted inference techniques.
• Harden edge-deployed models and secure data pipelines.
• Implement threat mitigation strategies specific to embedded and constrained systems.

This instructor-led, live training in Saudi Arabia (online or onsite) is aimed at intermediate-level machine learning and cybersecurity professionals who wish to understand and mitigate emerging threats against AI models, using both conceptual frameworks and hands-on defenses like robust training and differential privacy.

By the end of this training, participants will be able to:

• Identify and classify AI-specific threats such as adversarial attacks, inversion, and poisoning.
• Use tools like the Adversarial Robustness Toolbox (ART) to simulate attacks and test models.
• Apply practical defenses including adversarial training, noise injection, and privacy-preserving techniques.
• Design threat-aware model evaluation strategies in production environments.