AI terms, clearly explained
What does a term mean, and why does it matter for your organisation? For each term, a short definition, the explanation and what it means in practice.
Each term starts with a definition that stands on its own. Below it, you’ll find what it comes down to in practice, and where to read more.
AI agent
An AI system that takes steps on its own to reach a goal, rather than just answering.
Read the definitionAI hallucination
Output from an AI system that sounds convincing, but is wrong or made up.
Read the definitionAI Opportunity Audit
Upfront research that establishes, per process, which AI applications are feasible and what comes first.
Read the definitionAI readiness
How prepared your organisation is to put AI to work: data, processes, people and governance.
Read the definitionAI roadmap
A phased plan: which AI application when, who owns it and when you decide.
Read the definitionDeployer
The AI Act role of an organisation that uses an AI system built by someone else.
Read the definitionHigh-risk AI system
AI that helps make decisions about people, with the strictest requirements of the AI Act.
Read the definitionLarge language model (LLM)
The language model behind ChatGPT, Claude and Copilot: it predicts which text logically follows.
Read the definitionProcess mining
Using the logs in your systems to reconstruct how a process really runs.
Read the definitionPrompt injection
An attack using instructions hidden in data that an AI system processes.
Read the definitionRPA vs AI
Fixed rules that always do the same thing, versus AI that interprets but can vary.
Read the definition