Generative AI is artificial intelligence that creates new content, such as text, images, audio, video or code, in response to a written or spoken request. Instead of sorting or scoring existing data, it produces something that did not exist before, based on patterns it learned from very large amounts of training material.
How generative AI works
Text tools such as ChatGPT, Gemini, Claude and Copilot run on large language models. They write one small chunk of text at a time, each time choosing a likely next piece based on your request and everything written so far. Image and video generators work differently, often starting from random noise and refining it step by step towards something that matches the description.
Either way, the output is a prediction of what a good answer looks like, not a lookup of verified facts. That is why these tools can write fluent, confident text that is simply wrong, an error known as hallucination. Tools that search the web or your own documents before answering reduce the problem, but they do not remove it.
The quality of what you get depends heavily on what you give. A request with context (who the audience is, what the piece is for, examples of the style you want, facts to include) produces far better output than “write a blog post about boilers”.
Why it matters
Generative AI changes two things for UK businesses: how marketing gets made, and how customers find information.
On the production side, it speeds up first drafts, ad copy variations, product descriptions, image concepts, social captions, summaries of research and the first pass at data analysis. Used well, it frees time for the parts that need a person: knowing the customer, checking facts and making judgement calls.
On the discovery side, more people now get answers from AI assistants and from AI features in search results before they ever click a link. Those answers draw on web content, so being clear, accurate and cited across the web affects whether your business is mentioned.
The UK legal position needs attention. Section 9(3) of the Copyright, Designs and Patents Act 1988 has a specific rule for computer-generated works, but at the time of writing (October 2026) the government is reviewing how copyright should apply to AI, so ownership of purely AI-generated material is not settled. Advertising is clearer: AI-generated ad imagery and copy must still meet the CAP Code and must not mislead. An AI image that makes a product look better than it is can breach the rules just as a doctored photo would, and the ASA can act on it.
Common mistakes
- Publishing without checking. Invented statistics, wrong prices and made-up legal points reach live pages because no one verified the draft.
- Mass-producing pages. Using AI to publish hundreds of thin pages aimed at search terms runs into Google’s spam policies, regardless of how the pages were written.
- Losing your voice. Unedited AI copy tends to sound like everyone else’s. Customers notice.
- Pasting in confidential or personal data. Check what the tool does with your inputs before sharing client or customer information.
- Misleading visuals. Generated images of results, premises or products that do not match reality breach advertising rules and damage trust.
How to act on it
Use generative AI where it saves real time and where errors are easy to catch: outlines, first drafts, variations for testing, summaries and research prompts. Keep a person responsible for every published fact, claim and image. Write a short internal policy covering which tools are approved, what data must never go into them, and who signs off AI-generated content before it goes live. I have written more about using AI for marketing without hurting your SEO.
Then look at the other side: how AI tools describe your business when customers ask. Checking that, and making your site easier for AI systems to read and cite, is what my AI search optimisation service covers.