AI creative tools don't have malicious intent, they have statistical defaults. Trained on datasets that skew toward certain bodies, skin tones, lifestyles and cultural references, tools like Midjourney, DALL-E and AI copywriters reproduce those defaults unless you actively work against them.

The AI Representation Checker helps Media and Marketing teams catch that gap, at two points in the creative process. In pre-production, describe your campaign brief and intended AI tools and get a risk assessment across four dimensions: Visual Representation, Cultural Assumptions, Language & Tone, and Audience Inclusion, with specific prompting guidance to counteract each bias before a single asset is generated. In post-production, upload your finished AI-generated images and Claude visually analyses them against your stated audience and intent, surfacing what the tools defaulted to and what to fix or disclose before publishing.

Try it with this example or use your own:

• Campaign Name: ActiveLife: "Move More" OOH Campaign
• Brief: A national outdoor fitness campaign promoting a new range of gym wear and activewear. The campaign will feature people running, cycling, and doing yoga in outdoor urban settings. We want to show movement as joyful and accessible, not elite or performative. Large format OOH across UK cities plus social cutdowns.
• Target Audience: UK adults 28–50, all fitness levels including beginners, body-positive positioning, racially diverse urban population
• AI Tools: Image generation, AI copywriting
• Channels: Social media, Out-of-home (OOH), Digital display