Generative AI
Also called GenAI, gen ai, generative artificial intelligence
AI that creates new content, such as text, images, audio, code or video, rather than only sorting or predicting labels.
Generative AI is the broad term for AI systems that produce new content. Language models generate text and code; diffusion models and related systems generate images and video; other models generate speech, music and 3D objects. The content is new in the sense that it is composed fresh for each request, even though it is shaped entirely by patterns in training data.
The term is used to distinguish these systems from earlier, mostly predictive AI, such as spam filters, recommendation engines and fraud detection, which classify or score things rather than create them. In practice the line is blurry: a generative model can also classify, summarise and extract, and is now often the easiest way to do those tasks too.
Generative AI became mainstream in 2022 and 2023 with tools like ChatGPT, Midjourney and Stable Diffusion. It is now built into office software, search engines, design tools, coding environments and phones. Its strengths are speed and flexibility; its weaknesses include confident errors, inconsistent output, questions about training data and copyright, and the effort needed to check what it produces.
Example
A small bakery uses generative AI to draft its weekly newsletter, create a product photo of a new cake on a clean background, and write alt text for every image on its website, three different kinds of generated content.
Common mistake
Treating generated content as finished work. Generative AI produces plausible drafts quickly, but plausible is not the same as correct, on-brand or legally safe. Build a review step into any workflow where the output reaches customers.