Brand-safe AI image generation for performance ads

The reason most AI ad creative underperforms is uncanny-valley faces and inconsistent lighting. Both are solvable. The brands shipping AI creative that actually converts treat image generation as a compositing tool, not a hero-shot generator.

The workflow

Start from a real photograph. Use AI for variations — backgrounds, props, lighting — not for the hero subject. Approval rates double when faces and product remain photographic and only the surrounding scene is generated.

The brand guardrails

• Lock palette and typography in a Figma overlay applied after generation.
• Generate raw, then composite — never publish a model's output without human compositing.
• Reject any output with text in the image — generative models still get it wrong 30% of the time.
• Maintain a 'forbidden look' library so QA can compare against rejected aesthetics.

Tooling pick

Mid-journey for hero variations, Stable Diffusion fine-tuned on your brand for batch variants, Runway for animated extensions. Don't use any single tool for everything — each has a sweet spot and the difference shows in the final ad.

Measurement

Test AI-augmented vs photography-only at the asset-group level. Expect AI to win on volume and lose on hero CTR for the first quarter, then catch up as the team learns the workflow.