AI Literacy Essentials

Artificial intelligence (AI) is a broad term for computer systems that can perform tasks typically requiring human intelligence. It is important to distinguish AI from simpler forms of technology. A rules-based system follows pre-programmed instructions — for example, an email filter that routes messages based on keywords. Automation executes repetitive tasks without decision-making, such as auto-saving a document every five minutes. AI, by contrast, learns from data and can adapt its behaviour without being explicitly reprogrammed for every scenario. There are several types of AI relevant to the modern workplace. Machine learning (ML) systems identify patterns in large datasets and use those patterns to make predictions or decisions. Recommendation engines on streaming platforms, fraud detection in banking, and predictive maintenance in manufacturing all rely on ML. Natural language processing (NLP) enables machines to understand and generate human language — this powers chatbots, translation services, and voice assistants like Siri or Alexa. Generative AI is the most visible recent development. Systems like ChatGPT, Claude, and Midjourney can produce text, images, code, and audio that closely resembles human-created content. These models are trained on vast amounts of data and use statistical patterns to generate new outputs. They do not "understand" content the way humans do — they predict what comes next based on probability. In the workplace, AI appears in many forms you may already use daily. Email clients use AI to suggest replies and detect spam. Spreadsheet tools offer AI-powered forecasting. HR platforms use AI to screen CVs. Sales tools predict which leads are most likely to convert. The EU AI Act applies to all of these when they are used within the European Union, regardless of where the AI provider is based. Understanding what AI is — and what it is not — is the foundation of AI literacy. Not every piece of software is AI, and not every AI system carries the same level of risk. This distinction matters because the EU AI Act assigns obligations based on the type and risk level of the AI system being used.