What it means
Generative AI refers to AI systems that create new content, such as text, images, audio, code or video, based on patterns learned from large amounts of existing data. The output is produced fresh each time, which makes these systems flexible but also means results can vary and can be wrong.
Real-world example
A hospital's communications team uses a generative AI tool to draft plain-language versions of patient information leaflets. A medical writer reviews every draft against the original clinical guidance before it is approved, because the tool can simplify in ways that change the meaning.
Why it matters for AI adoption
Generative AI can speed up drafting, summarising and translation tasks across many roles, which makes it one of the most widely adopted forms of AI. But its outputs are plausible rather than guaranteed to be correct, so organisations need clear rules for review, data protection, copyright and transparency about AI-generated content.
Questions to ask
- Which outputs will be reviewed by a person before they are used or published?
- What data are staff allowed to enter into the tool, and where is it processed?