Practical guide

AI Product Photography Workflow: From Prompt to Final Asset

A strong AI product image starts with fixed product facts, a simple composition, one lighting direction, and a final manual check for labels and geometry.

Last updated: 2026-07-05

Comparison data

StageInputOutputReview gate
BriefProduct factsPrompt constraintsNo invented claims
ConceptText prompt1K draftComposition
RefineReference imageEdited draftProduct fidelity
FinalApproved prompt2K/4K imageLabels and edges
DeliverFinal fileCampaign assetUsage rights

Recommendations by scenario

New product without photography

Use text-to-image for direction, then replace invented details with a reference-guided pass.

Existing pack shot

Upload the pack shot and ask for environment, light, and surface changes only.

Architecture product context

Describe the space and lighting separately from the product constraints.

Concrete examples

  1. 01Keep the bottle shape, cap, and label hierarchy unchanged. Place it on pale blue glass with soft water caustics and a clean horizon.
  2. 02Create a top-down campaign still of this watch on brushed steel, one hard side light, precise shadow, no extra objects.
  3. 03Preserve the chair design. Move it into a minimal concrete gallery with late-afternoon light and neutral styling.

Limitations and pitfalls

  • AI output is not proof of physical product dimensions.
  • Small printed copy may need to be replaced in design software.
  • Reference editing can unintentionally change unprotected details.

Continue in Kansova

Sources and methodology

This guide uses the supplied provider documentation, current Kansova controls, and published Kansova credit rules. It avoids quality rankings that were not measured in a controlled test.