AI has moved from novelty to necessity in the design studio. What began as a playful experiment in concept generation has quickly evolved into a powerful, (albeit sometimes destabilising) engine for ideation, visualisation, and creative decision-making.
But as the technology accelerates, so does the tension: is AI a collaborator, a tool, or a threat? And maybe more importantly: what remains uniquely human in the design process when machines can make infinite variations in seconds?
These questions shaped our latest Spotlight session, where we brought together innovators who are embedding AI into the realities of the commercial fashion workflow, not as hype but as practice:
Sean Lane, Director, Digital Innovation & AI, Vans
Mattia Giorgi, Head of AI & Innovation, Gruppo Teddy
Nick Grills, Senior Product Manager, Marks & Spencer
Safir Bellali, Adjunct Instructor, ArtCenter/USC Iovine & Young Academy
Sylwia Szymczyk, Co-Founder & CEO, fashionINSTA.AI
🎥 Watch the full discussion below, and read on for the ideas shaping the next era of AI-assisted creativity.
Key Takeaways
1. Acceleration Meets Friction
AI is undeniably fast. It expands exploration, multiplies variations, and pushes ideation beyond human bandwidth. But acceleration also introduces new friction, particularly downstream.
AI gives you endless ideas, but it doesn’t tell you which one is worth pursuing.
Sean Lane, Vans
Teams now spend more time evaluating, filtering, and aligning than they once did generating. The bottleneck has not vanished; it has simply moved.
Bottom Line: AI generates ideas, but humans still decide what matters.
2. The Designer’s Role Is Shifting, Not Shrinking
Designers are not being replaced; they are being repositioned. AI is reducing repetitive sketching work but opening new roles that blend creativity, direction, and critical judgment.
We’re moving from making every mark to directing possibility.
Safir Bellali, ArtCenter
Hybrid roles are emerging: AI Design Curator, Digital Producer, Visualisation Lead, Prompt Specialist. Creativity is becoming as much about selecting and refining as creating from scratch.
Bottom Line: The designer becomes a conductor, not a casualty.
3. Protecting Brand DNA in an Instant World
When AI can generate thousands of looks, the risk is not a lack of variation but a lack of identity. What you feed the model determines what it outputs.
AI won’t give you identity. It will remix whatever you give it.
Sylwia Szymczyk, fashionINSTA.AI
Brands need to build proprietary datasets, style guides, prompt libraries, and output guardrails to ensure that work feels authentic rather than generic.
Bottom Line: Creative direction becomes a discipline of data curation.
4. Patterns, Feasibility & Technical Development
The biggest opportunity is not surface aesthetics, but compressing the gap between concept and creation. AI is beginning to:
- suggest pattern adjustments
- highlight manufacturability concerns
- propose material pairings
- scaffold early tech pack structures
- analyse SKU-level data
Using AI to catch feasibility issues at concept stage will be transformative.
Nick Grills, Marks & Spencer
Bottom Line: AI strengthens the bridge between design imagination and production reality.
5. The Risk of Photorealism Too Early
Once downstream teams see a polished, photoreal concept, they instinctively treat it as finished. This shifts buying behaviour, timelines, and expectations.
A beautiful render can create commitment too early. People see it and assume it’s real.
Mattia Giorgi, Gruppo Teddy
Brands are now using stylised modes or clear draft indicators to prevent premature decisions.
Bottom Line: Fidelity influences psychology and therefore it must be controlled.
6. A Narrative Bridge From Concept to Consumer
AI collapses the once disconnected stages of creation, storytelling, and consumer-facing imagery. The same visual logic that generates concepts can generate campaign narratives, retail visuals, and e-commerce adaptations.
For the first time, we can carry one coherent story from the designer’s mind all the way to the customer.
Sean Lane, Vans
This continuity was unimaginable a few years ago; it tightens alignment and strengthens brand storytelling.
Bottom Line: AI makes the creative pipeline narrative-first, not asset-first.
7. Measuring the Real Value of AI
Speed is easy to measure but no longer sufficient. The panel highlighted new KPIs:
- feasibility rate
- originality
- narrative consistency
- cross-team alignment speed
- reduction of dead-end directions
Speed matters, but without originality or feasibility, it’s irrelevant.
Safir Bellali, ArtCenter
Bottom Line: The real ROI of AI is quality, not quantity.
8. Competitive Edge When AI Levels the Playing Field
If every brand uses similar tools, advantage moves away from tool proficiency and toward taste.
Tools equalise. Taste does not.
Sylwia Szymczyk, fashionINSTA.AI
Differentiation will come from sharper editing, stronger creative direction, deeper consumer knowledge, and more courageous decision-making.
AI expands what is possible, but taste still defines what is exceptional.
Bottom Line: Human discernment becomes the new premium skill.
9. Data Integrity, AI Literacy & Organisational Adoption
Behind every successful AI workflow is a great deal of invisible labour:
- dataset cleaning
- copyright governance
- metadata and tagging
- prompt standardisation
- model tuning
- internal AI training
Organisations are discovering that adoption is as much about change management as creativity.
If your data isn’t good, your outputs won’t be good. It’s that simple.
Sylwia Szymczyk, fashionINSTA.AI
Bottom Line: The future belongs to teams who treat AI as a system, not a shortcut.
10. Ethics, Attribution & Future Governance
Fashion faces a unique ethical terrain: style scraping, authorship ambiguity, regulatory pressure, and the risk of over-automating creative labour.
Regulation such as the EU AI Act will require clarity on:
- training data
- AI-generated outputs
- ownership of AI-assisted design
- documentation and traceability
We are entering a world where knowing what went into the model will matter just as much as knowing what goes into the materials.
Bottom Line: Trust, attribution, and transparency will define the next phase of AI adoption.
So Where Does This Leaves Us?
AI is not colliding with fashion design; it is colliding with outdated assumptions about how fashion should work. The most successful teams will not be those generating the most images, but those asking the sharpest questions about identity, feasibility, impact and meaning.
At its best, AI does not replace creativity. It reveals it.
We’ll continue shaping these conversations on our platform throughout 2026 - bringing together designers, technologists, and makers who sit at the forefront of digital product creation. For more information, please visit pi.tv.
