What Is Generative AI?
Generative AI refers to machine learning models that can produce new data - rather than simply classifying or analysing existing data. Given a text prompt ("a red trainers product on a marble floor in warm natural light"), a generative image model can synthesise a photorealistic image that has never existed before.
The most commercially significant generative AI systems for ecommerce are image generation models (like Stable Diffusion and DALL-E), video generation models, and large language models (LLMs) for product descriptions. Together, they are transforming content creation from a manual, expensive process into an automated one.
How Generative AI Creates Images
Most modern image generators use diffusion models: they start from random noise and progressively "denoise" the signal, guided by a text or image prompt, until a coherent image emerges. This process is trained on billions of image-text pairs, giving the model a rich understanding of visual concepts.
For product-specific applications like Bryft, the models are fine-tuned on ecommerce imagery to ensure outputs are commercially usable: correct lighting, no artefacts, product integrity preserved.
Ecommerce Applications
- Generate lifestyle backgrounds for packshot products automatically
- Create campaign imagery for seasonal promotions at scale
- Produce model images for clothing without photo shoots
- Generate marketing copy and product descriptions alongside visuals
- Create video content from static images
Real-World Example
A home accessories retailer uses Bryft's generative AI to produce spring and summer campaign imagery across 800 products. The AI generates each product in four seasonal lifestyle contexts. What would have taken a team of photographers and stylists eight weeks is completed overnight, with consistent quality across all outputs.