Released in The Interline’s AI Report 2025, this executive interview with Graswald AI is one of an eight-part series that sees The Interline quiz executives from companies who have either introduced new AI solutions or added meaningful new AI capabilities into their existing platforms.
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Key Takeaways:
- In Graswald AI’s view, the future of AI in fashion lies in moving beyond general-purpose tools toward platforms built for real production needs. Generative models that can deliver brand-aligned content at scale are already replacing slower, less flexible methods like 3D and traditional photography.
- Based on their work with clients, they see the biggest gains when AI supports creative direction. Personalised, mood-specific imagery resonates most with consumers, and success depends on curation, consistency, and brand alignment, not volume alone.
- Graswald believes that as generative models improve, creative workflows will rely less on detailed prompts and visible interfaces. Tools that understand context and intent could soon shape outcomes in the background, enabling faster, more fluid content creation.
Where do you believe we currently are on the progression curve from AI as an extremely broad set of capabilities and promises, to AI as the foundation for applications and services that can deliver a measurable return on investment in well-defined areas?
We’re seeing a shift away from relying on broad, general-purpose AI toward solutions that are purpose-built for specific, high-value workflows. In creative industries like fashion, generic tools only go so far — what teams need are systems designed around their actual production needs.
In image generation—particularly in fashion (which is what I’ve been focusing on)—we’re seeing these models impact every stage of the value chain.
This is actually what inspired our solution, where we’ve taken the strengths of generative models and built a platform that solves a real pain point in fashion: producing content at scale without sacrificing brand quality or creative control.
My background is in 3D — and for years, that was the industry’s go-to for creating new visuals. But it’s slow, expensive, and rigid. Today, we’re replacing that with generative AI that’s not just faster and cheaper, but actually higher quality in many cases. That shift is what our product is built on.
How are consumer expectations around e-commerce evolving—and where are brands falling short?
Gen Z isn’t shopping the way older generations did. It’s not about searching for a specific item — it’s about discovering a mood, a moment, a vibe. Anyone can make a white t-shirt. What matters is the story around it. That shift puts huge pressure on brands to deliver more inspiring content, more often, and more tailored to individual audiences.
This is a both a big opportunity and a big challenge for brands, as it requires authenticity, personalisation, and consistency. Consumers want content that feels specific—like the perfect outfit for a summer party—not just another product listing. That means flatlays aren’t enough anymore. More than ever, brands need to show humans wearing clothing in specific scenes and moods.
But that kind of content is hard to produce at scale with traditional methods where you have complex logistics and long wait times.
I see with our clients daily how AI can help here, giving brands the ability to create personalised, high-quality product imagery at scale — using digital models, dynamic environments, and consistent styling — without the cost or lead time of a physical shoot.
How has content production for e-commerce changed? What impact is AI having?
The old model of content creation — seasonal campaigns, long lead times, massive crews — just doesn’t work anymore. Trends break on TikTok in the morning and are old news by evening. The brands winning right now are the ones who can create content at the speed of culture, Zalando is a great example here.
AI enables reactive, scalable content creation. It shifts the role of content creators from planning to curating. That means teams get to be faster, more flexible, and often smaller. You no longer need a 10-person crew.
Instead, you need one smart, creative operator who knows what good looks like, what the brand story is, and a high-performing, specialised AI tool (like ours) that gets them there.
What are the trade-offs brands face when using AI-generated content?
It’s a cultural shift as much as a technological one. Consumers expect more tailored content, and AI makes that possible. But there’s sensitivity around authenticity—brands worry about realism, accuracy, and trust. If something looks fake, it can damage credibility.
That’s why curation is so important. AI creators become gatekeepers—deciding what fits the brand and what doesn’t. From our clients, we know that consumers often prefer AI-generated content—especially when they don’t know it’s AI. The key is quality, relevance, and alignment with brand identity
So when you put the right creative controls in the right hands, you don’t lose authenticity. You enhance it — because now you can tell 100 stories, not just one.
Generative AI is evolving fast. How has that affected your approach, and what’s next?
Pace of innovation is probably the most important cultural aspect at Graswald AI.
Every week, we see new breakthroughs—new models, techniques, or workflows. We’re constantly testing and implementing them, always focused on solving real customer problems. We ask: will this help our customers create better, faster, or more affordably? If yes, it goes in. If not, we move on.
That said, two challenges still stand out: cost and compute time. As realism improves, models get heavier. But fast, low-cost iterations are essential for creative users. The next evolution will bring faster feedback loops and better UX, enabling brands to be even bolder and more expressive.
In the future, creativity will be the main differentiator in the Fashion e-commerce space, and AI tools that solve specific pain points will be the key to channeling and leveraging this.
What do you believe are the next steps for how AI in general is deployed and used? Is it more likely that AI will solidify its place as a new human interface paradigm the frontend of tools and workflows? Or is its future closer to what cloud infrastructure has become today – a quieter commodity that is still the foundation for the next generation of applications, but in a less obvious way than what we’ve seen over the last couple of years? Or is it both?
Both. Today, most desk jobs revolve around transforming data—analysing, enriching, and sharing it. Cloud made it scalable; UI made it accessible. Now AI, especially multimodal language models, is automating that transformation with minimal input.
These models are getting better at doing more with less context. A year ago, you needed elaborate prompts for a good output. Now, a few keywords or a link can yield equal or even superior results. In time, we won’t need interfaces in the traditional sense. AI will gain context from how we already work and interact with our human team. We may end up with tools that need no visible interface at all. Just input and intent.