Generative AI
In short. Generative AI is a type of artificial intelligence that creates new content, such as text, images, audio or code, in response to a prompt. It learns patterns from large amounts of data, and its outputs are designed to be plausible, so they need checking before anyone relies on them.
Last checked against its sources on 10 October 2026. How we write these.
Tools such as chat assistants and image generators are examples of generative AI. Given an instruction, they produce a draft email, a summary, a picture or a block of code that did not exist before.
For a small business, the value is speed on first drafts and routine work: summarising documents, drafting replies, preparing outlines, sorting information. It works best as an assistant whose output a person reviews.
The main limit is reliability. These tools generate likely-sounding text rather than verified facts, and they are not guaranteed to be accurate, so they can state false information confidently. Facts, figures, legal points and quotations should always be checked.
Data handling also matters. Before pasting customer or confidential information into a tool, check the provider's terms on storage and training use. A sensible approach is to start with low-risk tasks, set a simple rule for what may and may not be shared, and keep a person responsible for the final result.
Questions people ask
Is generative AI the same as ChatGPT?
ChatGPT is one product built on generative AI. The term covers a wider range of tools for text, images, audio, video and code.
Can generative AI be trusted to be accurate?
Not without checking. It can produce confident but wrong answers, so treat outputs as drafts and verify important facts.
Sources
- Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1) checked 10 October 2026