Product & Design
Concept ideation and moodboard generation
Generate visual concept directions and moodboards from a written brief, trend inputs, and brand references, giving designers a broader starting set to react to at the front of the development process.
40–60%
reduction in time to first concept set
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
Tommy Hilfiger ran an early pilot with IBM and the Fashion Institute of Technology in which AI generated silhouettes, colours, and prints from a library of the brand's own runway and product imagery, with designers treating the output as raw material rather than finished direction (FIT).
Copyright is the live risk. Check the terms of any image model you use for commercial rights and indemnity, and never prompt with a competitor's brand name or a named living designer's style.
Designers respond badly to AI presented as a replacement and well to AI presented as a faster mood-boarding tool. Frame it as removing the search-and-collect stage, which is the part most of them dislike.
Experiment starter: Run one real seasonal brief through both routes. Give the design team the AI concept set and their own, and have the buying director pick the four directions to progress without knowing which is which.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Experimentation FrameworkThis is an augmentation opportunity — see the relevant playbook section for how to approach it.More in Product & Design
Technical pack and specification drafting
Draft technical specification packs from a design brief and a library of prior specs — construction detail, measurements, materials, tolerances, and testing requirements — for a technologist to review.
Colourway and print variant generation
Generate colourway and print scale variants of an approved design, rendered on the product silhouette, so the team can review a wide option set before committing to physical strike-offs.
Sample review comment consolidation
Consolidate fit, quality, and design comments from multiple reviewers into a single structured amendment list per sample, deduplicated and grouped by the party who has to action it.
AI Transformation Playbook
Ready to assess your own opportunities?
The playbook gives you the full 150-opportunity directory, scoring tools, and 100+ templates for every stage of an AI transformation programme.