Foundations
It is the difference between software that answers a fixed set of questions and software that drafts a proposal, a reply, or a design. The output still needs review before it reaches a customer.
In plain terms
Generative AI is AI that produces new content, such as text, images, code, or audio, rather than only classifying or scoring existing data.
Also called GenAI.
Generative AI produces new text, images, code, or audio from a prompt. Older automation only copied, moved, or counted what already existed. Generative systems write the first draft, sketch the picture, or propose the next step.
The new part is also the risk. A generated paragraph can look finished and still be wrong, off-brand, or based on someone else's material. A useful rollout tells people what the system may generate, who checks it, and where the original file lives. Generation without a check is how confidential or wrong material leaves the building.
Think of it this way: Traditional software retrieves or transforms. Generative AI composes. It is the difference between a search engine finding a document and a copywriter writing a new one from scratch.
A property management company uses generative AI to produce tailored lease renewal letters from a simple data record, cutting manual drafting from 45 minutes to 2 minutes per letter.
A retailer uses generative AI to write product descriptions for 2,000 new items. The system drafts from the spec sheet. A buyer checks the claims about materials and origin before the text goes on the site. The draft saves hours. The check stops a false claim.
When the output needs to be original, varied, or adapted to context: drafts, summaries, design variations, and personalised communications at scale. When the output needs to be exact, deterministic, or auditable. Generative output must be reviewed before it reaches a customer in any regulated or high-stakes context.
You do not need to pick a model from this page. RaftLabs starts from the job: the documents, the decision, and what a wrong answer costs. You see a working version before a large build. The related work on our side is Generative AI development.
This sits with the other foundations terms on the glossary. The words under every AI conversation, from the model itself to the data it learned from. Worth reading next: Artificial Intelligence (AI), Machine Learning (ML), and Large Language Model (LLM).
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