Stop feeling excluded by technical language! Take your first step towards AI Act Art 4: AI Literacy.

We start with the AI tool you’re most likely to know — ChatGPT — and use it as a gateway to understanding how AI works in real-world organisational contexts. 

• You’ll see how the same model behaves differently in public, enterprise, and in-house deployments, and what those differences mean for privacy, governance, and compliance. 
• We’ll unpack common misconceptions, explore how data is handled in each setting, and highlight the ethical prompting practices that still matter even in tightly controlled enterprise environments. 
• By the end of this primer, you’ll have a clear, risk-aware foundation that will make the rest of the course easier to apply to your own work. 

A clear map of the new AI-driven workplace.

• This module makes sense of the technical changes reshaping even non-technical jobs.
• We cut through the tech-speak so you can finally see, in plain language what’s happening.  
• You’ll learn how today’s AI systems are built, and how the new digital infrastructure works, so you can work confidently alongside it instead of feeling lost in a maze of unfamiliar tech. 

AI isn’t just the chatbot you open in a browser, it’s woven into your email client, HR system, CRM, and even your meeting software. 

• This module shows you how to spot the different kinds of AI you’ll run into at work, from large language models like ChatGPT to the quiet, embedded AI that runs behind the scenes in everyday tools. 
• You’ll also learn how deployment choices - public, enterprise, or in-house affect data, security, and compliance, so you can work with AI features confidently and responsibly. 

Every time you use AI at work, your data goes somewhere, but do you know where? 

• In this module, you’ll follow the path your data takes, from your device to the cloud and beyond. 
• You’ll learn to read retention and training policies, apply privacy-by-design thinking, and decide what’s safe to share. You’ll also get clear on which data types are regulated and how to handle them, so you can use AI tools without putting your organisation, or yourself, at risk. 

AI can be powerful ... and risky. 

• In this module, you’ll learn how to spot the three biggest categories of risk: accuracy errors, bias, and security gaps. 
• We’ll unpack why these problems happen, how they can affect real-world decisions, and what you can do to reduce the chances of harm. 
• You’ll also learn how to connect each risk to the right safeguard, from human oversight to pre-deployment testing, so AI becomes an asset instead of a liability in your work. 

AI doesn’t run in a vacuum — it runs in environments with very different rules, risks, and controls. 

• In this module, you’ll learn how to tell the difference between public and enterprise AI platforms, understand on-premises, cloud, and hybrid deployments, and see how access controls shape who can do what. 
• We’ll also look at how vendor contracts (SLAs) affect AI performance, compliance, and security, so you can use AI systems in your organisation the right way from day one. 

AI projects succeed or fail based on communication, and this module gives you the tools to get it right. 

• You’ll learn how to translate business needs into terms technical teams can act on, make sense of AI documentation without getting lost in jargon, and ask questions that uncover risks before they become problems. 
• You’ll also learn how to bridge the most common misunderstandings between business and tech roles, so your projects run smoother and stay aligned with compliance standards. 

Knowing about AI is one thing, using it wisely in your own work is another. 

• This module shows you how to match AI’s capabilities to your role, redesign processes without losing human oversight, and build a practical risk checklist for your team. 
• You’ll also learn how to keep your AI knowledge fresh as tools and regulations change, so your AI literacy isn’t just a one-time achievement but a lasting professional skill. 

This feature explains GPT-5’s new “agentic” behaviour and how to control it for safe, effective workplace use.

• You’ll see how to set the right autonomy level for the task, use tool preambles to make reasoning visible, and adjust output length and depth with the new verbosity and reasoning effort settings.
• It’s a plain-language, practical guide to applying GPT-5’s latest features in real-world, non-technical roles.