Turn AI risk into organizational strength. Structured decision support is just a click away!

Start by turning “AI governance” into something concrete you can run. 

• We clarify the principles that drive trustworthy AI, define who does what across legal, risk, product, security, and audit, and map the full AI lifecycle so you can see where policies and controls actually live. 
• You’ll complete a role-based AI literacy matrix that helps your organization evidence EU AI Act Article-4 expectations and build a simple RACI for real decisions like intake, change control, and incidents. 
• This module aligns with AIGP Domain I (foundations, roles/collaboration, lifecycle policies) and previews the EU AI Act risk-tier model you’ll operationalize later, so leaders, DPOs, and managers leave with a shared language and audit-ready artifacts. 

Cut through the noise and see exactly what applies to you. 

• We translate the EU AI Act’s risk tiers and role-based duties into a simple obligations matrix, then show how existing laws—privacy, non-discrimination, consumer protection, product liability, and IP—shape day-to-day AI decisions in finance, healthcare, and other regulated settings. 
• You’ll learn to use global frameworks (OECD, NIST AI RMF, ISO/IEC) as ready-made control libraries, understand when GPAI and systemic-risk obligations matter, and assemble the evidence that auditors and regulators will expect. 
• The result is a practical rulebook you can run, with clear Article-4 literacy signals and AIGP-aligned competencies. 

Turn vague AI ideas into clear, governed decisions. 

• This module teaches you to spot prohibited practices, classify risk accurately, and complete a concise intake record that captures data sensitivity, decision stakes, and initial guardrails like human oversight, transparency, and logging. 
• You’ll run a practical triage lab, decide when FRIA/DPIA and other reviews are triggered, and file audit-ready evidence that feeds your AI inventory and oversight plan. 
• The result is a repeatable front-door process that meets EU AI Act Article-4 expectations and aligns with AIGP competencies for risk classification and deployment readiness. 

Turn AI governance from theory into a working system. 

• This module shows you how to choose the right governance model, define decision-making roles, and assemble a policy stack that covers AI use, procurement, incidents, transparency, and system deactivation. 
• You’ll map each policy to lifecycle stages and evidence requirements, and integrate AI governance into your existing privacy, risk, and security frameworks. 
• The result is a complete governance architecture with the documents and role clarity to meet EU AI Act Article-4 expectations and stand up to board or regulator review.

Whether you build AI models in-house or buy them from a vendor, governance starts at design. 

• This module teaches you how to define purpose, gather requirements, and embed human oversight from the outset. 
• You’ll learn to govern training and testing data, conduct bias and security checks, and document every step for audit readiness. 
• For vendor models, you’ll apply a due diligence process, add protective contract clauses, and evaluate technical documentation. 
• By the end, you’ll be able to approve AI models for release with the same rigour the EU AI Act expects from providers and deployers — meeting Article-4 literacy standards and protecting your organisation from hidden risks.

Once an AI system goes live, governance doesn’t stop — it shifts into continuous oversight. 

• This module shows you how to assess deployment readiness, implement human oversight protocols, and train users for safe operation. 
• You’ll design monitoring and maintenance plans to detect bias, drift, or performance issues, and handle serious incidents with proper documentation and timely reporting. 
• Finally, you’ll learn when and how to deactivate or localise systems to meet regulatory and ethical standards. 
• The result is a live operations governance plan that satisfies EU AI Act Article-4 literacy and keeps deployed AI under disciplined control. 

Not all AI models are equal — general-purpose AI models come with their own AI Act obligations, and systemic-risk GPAI faces even stricter rules. 

• This module explains how to identify GPAI in your organisation or supply chain, meet documentation and transparency requirements, and verify copyright compliance. 
• You’ll learn the extra steps for systemic-risk models, from adversarial testing to continuous monitoring, and integrate these duties into your procurement, vendor, and deployment processes. 
• The result is a governance approach that keeps your use of GPAI compliant, transparent, and safe — in full alignment with EU AI Act Article-4 literacy.

Transparency is more than a legal checkbox — it’s a trust signal. 

• In this module, you’ll learn when the AI Act requires disclosure, from chatbots to deepfakes, and how to design those notices so they’re legally compliant and user-friendly. 
• We’ll cover how to avoid dark patterns, integrate transparency into your policies and workflows, and keep evidence for audits. 
• By the end, you’ll have the tools to make AI transparency part of your organisation’s governance and user experience strategy, strengthening both compliance and trust. 

Governance is only as strong as its follow-through. 

• This module shows you how to set up oversight structures, run internal and external assurance processes, and keep decision-makers informed with the right metrics. 
• You’ll learn the AI Act’s incident reporting rules, practise handling a simulated system failure, and document every step for audits. 
• By the end, you’ll have the tools and processes to prove your AI systems remain compliant and well-governed — not just at launch, but throughout their lifecycle. 

Long-term AI governance success depends on culture. 

• This module shows you how to build role-specific training programs, incentivise responsible AI behaviours, and adapt governance for agile, AI-first environments. 
• You’ll learn to assess your organisation’s maturity level, set improvement targets, and scan the regulatory horizon for changes that demand a policy refresh. 
• The result is a governance culture that keeps pace with technology and regulation while meeting EU AI Act Article-4 literacy expectations. 

The final module brings everything together. 

• You’ll compile all your governance artifacts — from AI inventories and risk classifications to oversight logs and transparency records — into a single, indexed package. 
• You’ll learn how to cross-reference each piece to AI Act obligations, tailor it for different audiences, and present it confidently to a board or regulator. 
• By the end, you’ll have a complete governance pack that demonstrates EU AI Act Article-4 literacy in action and shows your organisation is ready for any audit or compliance review. 

This feature shows governance leaders how to integrate GPT-5’s new autonomy controls, transparency preambles, and output-tuning features into organisational policy.

• You’ll learn how to set default autonomy levels by workflow, require AI planning steps for auditability, and standardise output settings for different task types.
• It’s a governance-level view of GPT-5’s capabilities, helping you align AI operations with your organisation’s compliance and risk management standards.