Generative AI
Also called GenAI, gen AI
What is Generative AI?
Generative AI is a type of artificial intelligence that creates new content, such as text, images, audio, music or video, in response to a prompt. It learns patterns from very large training datasets, then produces original output that resembles that data. Chatbots, image generators and AI voice tools are all generative AI.
Different kinds of model sit behind different media. Large language models predict text one token at a time. Image and video tools usually use a diffusion model, which starts from noise and refines it step by step until it matches the prompt. Voice and music models work on audio waveforms or compressed audio tokens.
Generative AI is different from older 'predictive' AI, which sorts or scores existing data (spam filters, product recommendations). It is also different from automation, which follows fixed rules. Generative tools are probabilistic: the same prompt can give a different result each time, and the output can be wrong or invented.
Why Generative AI matters
For a small marketing team, generative AI cuts the time and cost of first drafts: captions, ad variations, backdrop images, voiceovers and music beds. Work that once needed a designer, a voice actor and a stock library can start from a few sentences.
The catch is quality control. Generative output can be generic, off-brand or factually wrong, so the businesses that get value from it give the model good inputs (brand facts, voice, examples) and check what comes out before it is published.
How to use generative AI in marketing
- Pick narrow, repeatable jobs first: caption drafts, ad copy variations, image backdrops or voiceovers.
- Give the tool real context: what you sell, who it is for, your brand voice and the facts it may use.
- Keep humans on the final check, especially for claims, prices and anything regulated.
- Label or disclose AI media where platforms or laws ask for it.
- Track results like any other content, and keep what performs.
Generative AI example
A bakery called Crumb & Co uses a language model to draft five caption options for a new sourdough loaf, an image model to make a soft kitchen backdrop behind a real product photo, and an AI voice to read a 20-second reel script. The owner edits the caption and checks the price before posting.
Generative AI FAQ
What is the difference between AI and generative AI?
AI is the broad field of software that performs tasks that normally need human judgment. Generative AI is the part of it that creates new content, rather than only classifying, predicting or recommending.
Is ChatGPT generative AI?
Yes. ChatGPT is a chatbot built on a large language model, which is a form of generative AI for text. Many such chatbots can now also create images and audio.
Can I use generative AI content commercially?
Usually, but check the terms of the tool you use and the rules where you operate. Copyright protection for purely AI-made work is limited in some countries, including the US, and you are still responsible for what the content claims.
Related terms
A large language model (LLM) is an AI model trained on huge amounts of text to understand and generate language, powering chatbots and AI writers.
A diffusion model is a type of generative AI that creates images, video or audio by starting from random noise and removing it step by step.
A prompt is the instruction or input you give an AI model, such as a question, a task or a description of the image you want it to create.
AI marketing is the use of artificial intelligence to plan, create, target and measure marketing, from writing copy to choosing who sees an ad.
Synthetic media is any image, video, audio or text created or substantially changed by AI, from AI voiceovers to generated photos and avatars.
An AI hallucination is false or made-up information that an AI model presents as fact, such as invented statistics, quotes, features or sources.