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.