Generative AI – or GenAI – is a type of artificial intelligence that creates new content—rather than just analyzing or classifying existing data.

Instead of answering “what is this?”, generative AI answers “make something like this.”

 

What Generative AI can create

  • Text: emails, stories, code, summaries
  • Images: illustrations, photos, designs
  • Audio: music, sound effects, voices
  • Video: clips, animations, synthetic footage
  • 3D & designs: models, layouts, product concepts

 

How it works (high level)

Generative AI models are trained on large amounts of data to learn patterns and structure. When prompted, they generate new outputs by predicting what should come next based on those patterns.

Common model types include:

  • Large Language Models (LLMs): generate text and code
  • Diffusion models: generate images and video
  • Generative adversarial networks (GANs): an older but influential approach
  • Multimodal models: work across text, images, audio, and more

 

Simple example

  • Traditional AI:
    “Is this email spam or not?”
  • Generative AI:
    “Write a professional email about a project delay.”

 

What Generative AI is not

  • It doesn’t “imagine” like a human
  • It doesn’t understand meaning or truth the way people do
  • It can generate plausible but incorrect content if not guided or checked

 

How it with other AI types

  • Generative AI → focuses on creation
  • Agentic AI → focuses on action and autonomy
  • Predictive/analytical AI → focuses on classification and forecasting

They’re often combined. For example, an agentic system might use generative AI to write code, messages, or plans as part of completing a goal.

Together, these form many modern AI systems.