Helping Great Companies Get Better at Compliance

Course Overview

This course guides you step-by-step to create your own clear and practical AI policy, tailored specifically to your organization's needs. You'll see practical examples of what to include to ensure your organizations successfully uses AI tools responsibly. You'll learn why having a clear AI policy matters, including what is allowed and not allowed under GDPR, cybersecurity, and AI compliance regulations. The course also explains how to set rules that keep humans involved, monitor AI effectively, and prevent potential harm.

By the end of this course, you'll be able confidently draft your own AI policy without needing external help. To make this even easier, you'll receive a downloadable template to get started quickly. This template can be customized to match your organization's specific situation, reducing risk and supporting responsible innovation.

 

Who Is This For?

This course is ideal for professionals responsible for creating, implementing, or overseeing AI governance within their organization, including:

  1. Compliance & Risk Managers – Defining AI policy frameworks and ensuring alignment with the EU AI Act, GDPR, and internal controls.
  2. Legal & Data Protection Officers – Managing regulatory risk, reviewing AI use cases, and overseeing data protection compliance.
  3. IT & Security Leads – Embedding cybersecurity and access controls into AI systems and ensuring secure development practices.
  4. Product & System Owners – Overseeing the design, deployment, and monitoring of AI systems used across business functions.
  5. Procurement & Vendor Managers – Evaluating AI systems and ensuring third-party tools meet governance and risk requirements.
  6. HR, Training & Ethics Leads – Delivering AI-related training and fostering a culture of responsible and ethical AI use.

 

Modules

  • Starting Your AI Policy: Why, Who, and What - Learn how to define the purpose, scope, and ownership of your AI policy to ensure accountability and organizational alignment from day one.
  • Definitions - Establish a shared language by clearly defining core AI concepts.
  • What’s Allowed: Defining Authorized AI Uses - Set clear boundaries on what AI tools and use cases are permitted, and implement controls for approval, data protection, and appropriate use.
  • Know the No-Go Zones: What AI Is Not Allowed For - Identify prohibited AI applications like social scoring, manipulative systems, and unauthorized biometric use to prevent unethical or illegal practices.
  • Defining Your AI Principles: The Values Behind the Policy - Build the ethical backbone of your policy by outlining enforceable principles like transparency, accountability, and fairness.
  •  What’s Ethical AI? How to Set the Standard in Your Policy - Translate ethical commitments into actionable policy standards that protect human dignity and reduce the risk of harm or bias.
  • How to Meet Cybersecurity Standards in Your AI Policy - Integrate strong security practices aligned with NIS2, including access controls, secure development, and incident response readiness. 
  •  Integrated AI Risk Assessments: Staying Compliant - Apply required assessments (FRIA, DPIA, and cybersecurity) to evaluate AI system impacts and ensure legal compliance.
  •  Risk and Compliance Monitoring - Monitor AI performance over time, assign roles for oversight, schedule audits, and ensure early detection of emerging risks.
  •  What Happens After Launch? Managing the AI Lifecycle in Your Policy - Define post-deployment responsibilities like auditing, updates, version control, and system decommissioning to maintain compliance.
  •  How to Define Incident Reporting and Response in Your AI Policy - Create a structured process for reporting, investigating, and responding to AI incidents that protects your organization and stakeholders.
  •  Who Watches the AI? Building Oversight into Your Policy - Assign clear human oversight roles using Human-in-the-Loop or Human-on-the-loop models to ensure accountability in high-impact AI decisions.
  •  Who Needs AI Training? How to Define It in Your Policy - Develop training structures for general staff and specialists, covering AI use, legal obligations, and ethical risk recognition.
  • Community Engagement and Transparency: What to Include in Your AI Policy - Define how your organization will communicate AI use, offer disclosures, and provide public-facing transparency mechanisms. 
  •  What If Someone Breaks the Rules? How to Enforce AI Governance - Outline enforcement procedures with disciplinary steps, contractual clauses, and escalation paths for internal and third-party violations.
  •  When and How to Update Your AI Policy - Schedule annual reviews, enable rapid policy updates after incidents or regulatory shifts, and maintain version control and feedback loops.
  • Annexes and Appendices: Tools to Support Your AI Policy - Provide operational resources like templates, glossaries, checklists, and inventories to help teams apply your policy effectively.

Lessons

  1. Chapter 1

     Poglavlje 1

     AI Policy Step By Step

  2. Chapter 2

     Poglavlje 2

     Defining Your AI Principles: The Values Behind The Policy

  3. Chapter 3

     Poglavlje 3

     Annexes and Appendices: Tools to Support Your AI Policy

  4. Chapter 4

     Poglavlje 4

     What's Allowed: Defining Authorized AI Uses

  5. Chapter 5

     Poglavlje 5

     How to Meet Cybersecurtiy Standards in Your AI Policy

  6. Chapter 6

     Poglavlje 6

     Defining Key Terms: What to Include and How to Say It

Why Register?

  • Build a complete AI policy – Learn how to draft, implement, and enforce a fit-for-purpose AI governance policy from start to finish.Ensure GDPR compliance – Learn how to draft and enforce data processing agreements effectively.

  • Stay ahead of global regulations – Get guidance aligned with the EU AI Act, GDPR, and NIS2 to future-proof your compliance efforts.

  • Access ready-to-use templates – Download customizable tools like AI risk classification tables, assessment checklists, and incident response guides.

  • Improve risk detection – Learn how to classify AI systems, monitor compliance, and manage lifecycle risks effectively.

  • Improve risk detection – Learn how to classify AI systems, monitor compliance, and manage lifecycle risks effectively.

  • Improve risk detection – Learn how to classify AI systems, monitor compliance, and manage lifecycle risks effectively.

  • Improve risk detection – Learn how to classify AI systems, monitor compliance, and manage lifecycle risks effectively.

Reach your full potential.

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