Image-to-Image is an AI generation workflow that takes an existing image as input and transforms it into a new image based on text prompts, style references, or other conditioning inputs while maintaining structural or compositional relationships from the source. It allows creators to use existing imagery as a foundation while directing how it should be modified, reinterpreted, or stylistically transformed.

The technique is used for style transfer, where an image is reimagined in a different artistic style; compositional variation, where the basic layout is preserved but details are changed; refinement of AI-generated outputs that need adjustment; and adaptation of reference imagery into final production assets. Image-to-image workflows offer more control than pure text-to-image generation by providing visual structure as input, reducing the unpredictability of starting from random noise while still allowing creative transformation.

Image-to-image generation has become a core workflow in professional AI-assisted creative production, allowing creators to iterate on compositions, explore variations, and refine outputs toward specific goals. Understanding when to use image-to-image versus text-to-image helps creators work more efficiently by choosing the workflow that provides the right balance of control and creative freedom for each task.