20/09/2023
Generative AI: Unlocking the future of fashion:
How the foundation models and generative AI can be used across the fashion value chain
1) Merchandising and product:
- Convert sketches, mood boards, and descriptions into high-fidelity designs (for example, 3-D models of furniture and jewelry).
- Enrich product ideation by collaborating with AI agents that generate creative options (for example, new ideas, variations) from data (for example, past product lines, inspirational imagery and style).
- Customize products for individual consumers at scale (Eg., eyeglasses based on facial topography).
2) Supply chain and logistics:
- Support negotiations with suppliers by compiling research.
- Augment robotic automation for warehouse operations and inventory management through real-time analytics (Eg., insights enabled by augmented reality, or AR).
- Tailor product return offers based on individual consumers.
3) Marketing:
- Identify and predict trends to improve targeted marketing from unstructured data (for example, consumer sentiment, in-store consumer behavior, omnichannel data).
- Automate consumer segmentation at scale to tailor marketing initiatives.
- Generate personalized marketing content based on unstructured data from consumer profiles and community insights.
- Collaborate with AI agents to accelerate content development and reduce creative blocks for in-house marketing teams.
4) Digital commerce and consumer experience:
- Structure and generate sales descriptions based on past successful sales posts.
- Personalize online consumer journey and offers (for example, web pages, product descriptions) based on individual consumer profiles.
- Tailor virtual product try-on and demos to individual consumers (for example, clothing try-on, styling recommendations).
- Enhance intelligent AI agents (Eg, conversational chatbots, virtual assistants) and self-service to address advanced consumer inquiries (for example, multilingual support).
5) Store operations:
- Optimize store layout planning by generating and testing layout plans under different parameters (for example, foot traffic, local consumer audience, size).
- Optimize in-store labor to avoid bottlenecks such as gaps in staff allocation and theft detection through real-time monitoring of video data.
- Support AR-assisted devices to better inform workforce in real time on product (for example, condition, assortment, inventory, recommendations).
6) Organization and support functions:
- Coach sales associates to sustain successful “clienteling” relationships via real-time recommendations, feedback reports, and high-value consumer profiles.
- Develop individualized training content for employees based on role and performance.
- Enable self-serve and automate support tasks (Eg. HR, Accounting, Legal).
Read more:
https://www.mckinsey.com/industries/retail/our-insights/generative-ai-unlocking-the-future-of-fashion
While still nascent, generative AI has the potential to help fashion businesses become more productive, get to market faster, and serve customers better.