Generative AI (artificial intelligence) is the branch of AI that produces new content rather than simply classifying or predicting. Its models are trained on enormous amounts of data and learn patterns in language, images, or sound. When you give it an instruction—called a prompt—it generates a response consistent with those patterns. Models that work with text are known as LLMs (Large Language Models).

Why does it matter?

For a marketing team, generative AI speeds up tasks such as writing email subject lines, message variations, product descriptions, or data summaries. What used to take hours can now take minutes.

It's important to know your limits:

• It can make mistakes. Sometimes it generates information that sounds correct but isn't. That's why it's a good idea to review what it produces.
• It doesn't know your business on its own. A generic model doesn't know who your customers are or what they bought, unless you provide that context.
• Quality depends on instructions and data. The clearer the request and the better the background information, the better the result.

Story mode

Lucía, who works at an online sports store, asks a generative AI tool to draft an email for her winter collection. The text is correct, but generic—it could work for any store. She then tries a tool connected to her store’s data, which writes a personalized message for each customer based on their previous purchases. The technology is the same; the difference lies in the context.

How to Use It with Data4Sales

• Orbis Creative uses generative AI to write a unique message for each customer based on their data.
• Orbis Copilot answers questions about your data using natural language and generates automatic reports.
• In both cases, AI works based on a 360° profile of your customers, not on assumptions.

Related terms

• Context-Aware AI
• AI Co-Pilot
• Hyper-personalization
• Orbis