Jargon Buster / Generative AI
Generative AI.
AI & AutomationAI that creates new text, images, audio, video or code in response to plain-language instructions.
What is generative AI?
Generative AI is artificial intelligence that creates new content, such as text, images, audio, video or code, in response to instructions, based on patterns learned from very large amounts of training data.
Tools such as ChatGPT, Claude and Gemini are the best-known examples. You describe what you want in plain language and the system produces a draft, an image or an answer in seconds.
Why it matters
Generative AI drops the cost of a first draft close to zero. Proposals, job adverts, product descriptions, meeting summaries and replies to routine emails can all start from a decent draft. That is a real productivity gain for a small team. It also means your competitors can produce the same volume of generic content, so the advantage moves to what only you have: your expertise, your data, your customer stories and your judgement.
The main types
- Text generation Large language models write, summarise, translate and answer questions.
- Image generation Image models create or edit visuals from a description, useful for concepts and drafts.
- Audio and voice Models generate speech, transcribe calls and clean up recordings.
- Video generation Models create short clips from text or images, improving quickly but still uneven.
- Code generation Models write and explain software, from spreadsheet formulas to full applications.
The honest view
Generative AI produces the likely answer, which is another way of saying the average one. That makes it excellent for drafts, summaries and variations, and weak at original insight or anything that depends on facts it was never given. Unchecked, it also invents details with total confidence.
The overhyped use is publishing AI content at scale and hoping for traffic. The underrated uses are internal and dull: turning call notes into actions, drafting a proposal from a brief, tidying messy data, answering staff questions from your own handbook.
What to do about it
Pick three internal tasks that take someone at least an hour a week and trial a business plan of a mainstream AI tool on them for a month. Check its data settings so your inputs are not used to train public models. Write a one-page usage policy covering what information may go in, which outputs must be checked by a person, and who is accountable for anything that reaches a customer.
Related terms.
Large Language Model (LLM)
An AI system trained on huge amounts of text that can write, summarise, answer questions and follow instructions.
AI & AutomationSee more HHallucination
When an AI model states something false or invented with complete confidence.
AI & AutomationSee more PPrompt Engineering
The practice of writing clear, structured instructions so an AI model gives accurate, useful output every time.
AI & AutomationSee more TTone of Voice
How a business sounds in writing and speech, defined so everyone communicates in a consistent, recognisable way.
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