A recent conversation with a new tech entrant to the market got me thinking.
They were asking the questions any ambitious tool provider asks early on: what are brands actually struggling with, what do they want, what's getting in the way? And as I prepared for the call — drawing on the last year of events, panels, roundtables and research conversations across fashion, footwear and retail — I realised we've been sitting on a genuinely unusual vantage point.
At a moment when the market is more saturated with new tools and providers than it has ever been, and when the pace of change is making it harder for brands and builders alike to know where to focus, we might actually be holding something useful.
This is an attempt to share it more openly. Not as a definitive study, but as an honest synthesis of what the people closest to the work are actually saying.
If it feels obvious to you – good. It probably means you're already asking the right questions.
Something has shifted in the last twelve months.
I've spent a good part of that time in rooms with brands — at events, in research calls, in roundtables where people say things they wouldn't put in a press release. Across fashion, footwear and retail. Across planning, design, product creation and sourcing. Across companies ranging from five-person studios to some of the biggest names in the industry.
And their questions have changed.
Not long ago, conversations started with possibility. What could this tool unlock? What would this tool do for our bottom line? Which emerging tools might reshape how our product gets made?
There was real energy in those discussions. Sometimes excitement. Sometimes anxiety. Often both at once. But increasingly, the questions feel different.
Less: What can this do?
More: How would this actually work here?
It sounds like a small shift, but I don't think it is. I think it marks a meaningful change in where brands are in their relationship with technology, and it has real implications for anyone building tools for them.
The demo is no longer the hard part
Fashion doesn't have a shortage of innovation. If anything, it has too much of it.
In conversation after conversation, whether I was sitting with planners, designers, adopters, champions, sceptics and more, it's become obvious that teams aren't struggling to find compelling tools. They're struggling to figure out what to do with them once the shiny demo is over.
One senior figure at a major sportswear brand put it plainly: the challenge isn't getting leadership excited about a new capability. It's getting the same leadership to understand what needs to change structurally before that capability can actually land. Get the structure right, and culture tends to follow. Try to change the culture first, without changing the structure, and people will quietly revert to whatever works fastest.
Another, from the planning side of a global fashion group, described spending months trying to implement an AI-powered forecasting tool, only to realise that the real blocker wasn't the model, but the data feeding it. Inconsistent, incomplete, and siloed across systems that had been layered on top of each other for years.
'Garbage in, garbage out'. It's the oldest phrase in the industry, but it's still the most relevant one.
The questions brands are now asking
If you're building a tool for the fashion industry right now, here is what brands are actually trying to figure out. Not in theory, but in practice, and today.
- Does this fit into how we already work?
This came up constantly. Not "can we eventually reshape our process around this", but "does this slot in, or does it demand that we rebuild everything around it?" The appetite for workflow disruption is lower than it's ever been. Teams are stretched, budgets are tighter, and the bar for "is this worth the upheaval?" has risen significantly.
One director described evaluating several AI tools over a twelve-month window. The question that knocked most of them out wasn't capability, but integration. Does it talk to our ERP? Does it talk to PLM? Does it work alongside our 3D process? Can it read our existing data structures?
Ultimately, will this just mean maintaining yet another parallel system?
- Who owns this internally?
Brands are increasingly aware that buying a tool is the easy bit. It is the implementation of the tool where things go quiet. In roundtable after roundtable, the same tension surfaced: IT wants to own it, but doesn't understand the business need. The business team that wants it doesn't have the technical capability to implement it. And somewhere in the middle, the project stalls.
More than one brand described successful pilots that never scaled, not because the technology failed, but because no one had been clearly designated to own the transition.
The pilot team moved on to other priorities. The tool quietly got parked.
- What does success actually look like in six months?
This is the question that most vendor conversations still don't answer well. Brands know what a good demo looks like. What they're increasingly asking for, but not always getting, is clarity on what the journey from demo to embedded operational tool actually involves. What internal change does that require? What does the first 90 days look like? What are the realistic milestones?
A design lead I spoke with made the observation simply: "Every tool looks good in a controlled environment. The question is what happens when it meets our actual process."
AI has matured. The conversation has too.
Twelve months ago, AI conversations in fashion were suspended somewhere between fascination and fear. Would it replace designers? Homogenise creativity? Undermine the human judgement that the industry runs on?
Those questions haven't disappeared, but they have moved to the background. The foreground now is far more operational.
Can AI reduce the volume of repetitive admin that's eating into creative time? Can it make forecasts more reliable in environments where historical data is incomplete or misleading? Can it help smaller teams — already stretched — do more without burning out?
At an AI and design panel earlier this year, a senior product manager at a major retailer made the observation that AI's biggest early win in their organisation wasn't image generation or design ideation. It was helping non-designers understand what a design actually looked like before samples were made. Photorealistic renders, generated quickly, that gave leadership teams a shared visual language earlier in the process — and reduced the expensive late-stage changes that happen when people realise they've been imagining different things.
Not glamorous, but enormously practical.
That pattern kept repeating. The strongest AI use cases coming out of real conversations aren't the ones that make for the best conference slides. They're the ones that quietly remove friction from processes that have always been more manual, more time-consuming, and more error-prone than they should be.
Fashion is moving beyond AI theatre. The brands that are getting real value are the ones asking not "what can AI do?" but "where is the actual pain in our process, and can AI help with that specific thing?"
The governance question nobody wants to talk about
There's a conversation happening in most brands that rarely makes it onto a conference panel. It goes something like this:
The tool looks great. Legal has questions. IT has concerns. The data team wants to know where the information is going. And the brand team is worried about what happens to IP.
Particularly among premium and heritage brands, the governance conversation is now central to any technology evaluation. Not an afterthought. Not a compliance checkbox. A genuine blocker.
Several large brands described building internal AI applications rather than using third-party generative tools — specifically because of IP and data security concerns. Sending confidential designs through an external model, when those designs are two years from market, isn't a risk they're willing to take. More than one described walking away from vendor conversations because the provider was simply unwilling to operate within the data privacy constraints the brand required.
This isn't a niche concern. It's a pattern. And it means that for many tools, the question isn't whether the technology works. It's whether it can work within the security and governance constraints that serious brands require.
Speed matters. But "don't break the brand" matters more.
Not everyone is in the same place and that matters
One of the most important things to understand about the fashion and footwear industry right now is how unevenly digital maturity is distributed across it.
Some brands have been running sophisticated 3D workflows for a decade. Others are still working from flat sketches and spreadsheets. Some have dedicated innovation teams, internal AI builds, and clear digital roadmaps. Others are trying to figure out what tool to start with and whether they can afford the time to learn it.
This isn't just a story about big brands versus small ones, though scale is part of it. It's about culture, legacy, category, and how much organisational permission exists to try something new. A performance sportswear brand with a mandate to innovate exists in a fundamentally different environment to an artisanal heritage business where the founding identity is built on craft and continuity.
The implications for technology providers are significant. A tool built for the most digitally mature brands — sophisticated data infrastructure, dedicated 3D teams, agile workflows — will fail to land with the majority of the market. And the majority of the market is not the most digitally mature brands.
This came up repeatedly and with some force when I spoke with smaller and mid-sized companies. The tools, the infrastructure, the support – much of it has been built for the large players. Pricing tiers assume enterprise budgets. Onboarding assumes dedicated technical resource. Implementation support assumes someone internally who already understands the workflow being replaced. For a smaller brand where a single designer might be covering creative, development, and 3D, none of those assumptions hold.
The brands that described the most successful technology partnerships were the ones where the provider had genuinely understood where they were on the journey and met them there. Not with a dumbed-down product, but with an honest conversation about what was needed before the tool could work, and a willingness to support that process rather than hand over a login and disappear.
In practice, that often means the real differentiator isn't the product itself. It's the onboarding, the support, the change management. The human relationship that sits around the technology and makes it actually stick.
What this means in practice
The observations above look different depending on which side of the table you're sitting on. So rather than separate conclusions, here are the questions that matter most, for builders and buyers alike.
If you're building
Fashion doesn't need more features. It needs more understanding. Not understanding in the abstract, "we know fashion is complex and fast-moving", but specific, operational, granular understanding of how fashion businesses actually function. What a merchandising calendar looks like. Why a brand can't just "switch suppliers." Why the person who wants the tool is rarely the person who signs it off.
The tools gaining real traction aren't necessarily the most technically impressive. They're the ones that feel built by people who've spent real time inside fashion businesses, and who are honest about what their technology actually requires of the organisation adopting it.
A few questions worth sitting with before you build or go to market:
- Are we solving a problem brands actually have today — or one we think they should care about?
- Does this integrate into existing workflows, or does it require brands to rebuild around us?
- How much change management are we quietly asking organisations to take on — and are we being honest about that?
- And critically: who is this actually built for? The 20 most digitally advanced brands in the world, or the thousands who are trying to figure out where to start?
That last question matters more than it might seem. There is a significant and largely unaddressed commercial opportunity in the mid-market — brands that are digitally willing but chronically underserved by tooling built for enterprise. They move faster, are more open to genuine partnership, and represent a much larger share of the industry than the flagship names that tend to dominate case studies.
The founding stories that land with them lead with the problem, not the product. Not "here is what our technology can do" but "brands keep telling us this is broken, and we've built something that specifically addresses that."
If you're buying
Most technology projects in fashion don't fail because the ambition was wrong. They fail because the readiness — organisational, technical, structural — was overstated. The capability was there, but the conditions for it to succeed weren't.
The questions that tend to get skipped in the excitement of a good demo are usually the most important ones:
- What problem are we actually trying to solve, and is this the right tool for that specific problem?
- Do we have the data foundations this tool requires to work properly?
- Who owns implementation internally, and do they have the bandwidth and authority to see it through?
- What does success look like in six months, and how will we measure it?
- What happens if this doesn't work as expected? How hard is it to exit?
There is also a harder question that brands rarely raise in vendor conversations but probably should: what do I need to have in place before this tool can work?
The honest answer to that — data quality, internal ownership, team capacity, systems integration — is often the most useful thing a provider can tell a prospective customer. The ones willing to have that conversation upfront tend to be the ones worth working with.
The shift that matters most
If I had to name the single biggest change in how brands are approaching technology right now, it's this:
They're not searching for the most impressive tool.
They're searching for the right partner.
Someone who understands the hard part. Who doesn't disappear after the demo. Who is honest about what their technology requires of the organisation adopting it. Who has thought seriously about integration, change management, and what realistic success looks like. Not just in the best-case scenario, but in the messy, under-resourced, competing-priorities reality that most fashion businesses operate in.
That's a higher bar than it used to be. And it's the right one.
The next chapter won't be written by whoever builds the best tool. It'll be written by whoever best understands the people who have to use it.
Editor's note: This piece draws on research interviews, roundtable discussions, event sessions and ongoing conversations conducted across fashion, footwear and retail over the past twelve months — including brands, studios, technology providers and independent practitioners across Europe Asia and the US.
