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AI glossary · Foundations

Generative AI

Generative AI: Generative AI is a class of AI models that create new content, including text, images, code, audio, and video, in response to a prompt. Chat assistants like ChatGPT, Claude, and Gemini and image tools like Midjourney are generative AI.

Most AI before 2022 was predictive: it classified, scored, or ranked things that already existed. Generative AI produces something new. Ask for a project status email, a logo concept, a SQL query, or a voiceover, and the model composes it on the spot by predicting what should come next, one piece at a time.

Under the hood, text tools are large language models and most image tools are diffusion models, but you interact with both the same way: describe what you want in plain language. The quality of what you get depends heavily on how specific you are about audience, purpose, format, and constraints.

The limits matter as much as the capabilities. Generated text can be fluent and wrong. Generated images can carry the biases of their training data. Generated code can look correct and fail on edge cases. And anything you paste in may leave your organization, so check your company's policy before sharing confidential material.

Example at work

A marketing manager at a home services company drafts a month of social posts in one sitting: she pastes last quarter's best-performing posts as examples, describes the tone, and asks for twelve variations by theme. She then edits every post, removes two claims the model invented, and generates matching images in Canva.

Why it matters

Generative AI is the reason AI moved from a data science department to your desktop. The skill that pays off is not learning to code. It is learning to brief the tool the way you would brief a smart new hire, then reviewing its work with the same care.

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