Generative AI
AI systems that produce new content (text, images, code, audio) rather than just classifying or predicting from existing data.
Quick answer
What is Generative AI?
AI systems that produce new content (text, images, code, audio) rather than just classifying or predicting from existing data.
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Generative AI is the broad category for AI that creates new outputs. Large language models (GPT-4, Claude, Gemini) generate text. Diffusion models (Stable Diffusion, DALL-E) generate images. Code models (Copilot, Cursor) generate code. The defining shift from older "predictive AI" is that the output isn't a label or number. It's open-ended creative content.
For Salesforce: generative AI use cases include draft email replies, case summaries, knowledge article creation from resolved tickets, sales call summaries, prompt-driven CPQ quote building, and natural-language reporting. The Einstein GPT / Agentforce wave is Salesforce's productized generative-AI offering.
The line between "generative" and "agentic" is increasingly blurred. A pure generative AI just produces content in response to a prompt. An agentic AI takes actions and uses tools. Many production systems combine both, the LLM generates a response, then the agent layer decides whether to send it, log it, or escalate.
Related terms
Browse all terms- LLM (Large Language Model)A neural network trained on massive text corpora to predict and generate text, the foundation behind ChatGPT, Claude, Gemini, and modern AI assistants.
- Agentic AIAI systems that autonomously pursue goals using tool calls and multi-step reasoning, distinct from generative AI (which produces content) or predictive AI.
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