In plain English
Generative AI is AI that creates new content. The category includes text generation (ChatGPT, Claude, Gemini), image generation (Midjourney, DALL-E, Stable Diffusion), code generation (GitHub Copilot, Cursor), and increasingly audio and video. The "generative" part is the difference from classification AI, which just categorises existing content.
For SME business use, the text-generation flavour is where most real value lives. Drafting personalised replies. Summarising long documents. Generating reports and analyses. Writing draft content (proposals, contracts, marketing copy) that humans polish. Translating. Explaining technical content to non-technical audiences.
What generative AI is great at: handling variability, drafting first versions, processing language at speed. What it's bad at without help: accuracy on specific facts, current information (training cutoffs apply), maths on long numbers, certainty (it can confidently produce wrong outputs).
The production pattern that works for SMEs: generative AI drafts, humans review. The AI handles the volume; the human handles the quality control. This works in customer comms (AI drafts reply; human approves before send), content production (AI drafts blog post; human edits and adds expertise), and document processing (AI generates a summary; human verifies before action).
Where generative AI is overhyped for SMEs: replacing creative work, replacing strategic decisions, replacing customer relationships. It augments the people who do those things; it doesn't replace them.
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