AI Literacy
AI literacy is the set of knowledge and skills people need to understand what AI is, how it works, how to use it effectively, and how to judge its outputs and risks.
AI literacy doesn't require technical expertise. For most people, it means knowing what AI tools are good and bad at, how to give them clear instructions, when to check their work, and what information should never be shared with them. Without that foundation, people tend to either avoid AI entirely or trust it too much. Regulation is also paying attention. The EU AI Act, for example, asks organizations that provide or use AI systems to take steps to ensure sufficient AI literacy among their staff.
AI literacy is different from general AI training on a specific tool. Tool training shows people which buttons to press. Literacy helps them make good decisions as tools change. It works best when tied to real tasks in each role. Different roles need different depth. Leaders need enough understanding to set direction and manage risk, while frequent users need hands-on skill with the tools they rely on.
Key parts
Core concepts. What AI is, how models are trained, and why they can be wrong.
Practical use. Writing clear prompts and fitting AI into everyday tasks.
Critical evaluation. Checking outputs for errors, bias, and made-up information.
Responsible use. Protecting data and following policies on acceptable use.
