Welcome back to the Interline Podcast for our first episode of 2026. Now, we have listeners and readers everywhere in the world, so I won’t pretend that everyone’s beliefs and schedules line up with mine, but I hope you’ve recently been able to take some time out. For me, the end of December holidays and the slow roll into January are the one real chance I get to pause and reflect. So this is a time of year that I really look forward to a lot.
By the time you listen to this, we’ll be in 2026. So hopefully I’m catching you in a similarly pensive mood, even if you weren’t able to take a break. And I hope you’re ready to join me on a bit of a trip back through 2025 and look forward to what might be coming in 2026. I was tempted to try and do a ‘year in review’ podcast solo to compliment the piece that I write for the website every year. But then I realised that, while I do have a good vantage point on what’s happening front of house and behind the scenes with fashion technology, that doesn’t give me eminent domain over analysis and predictions. I’m not always right. So for this show, I brought in someone who moves in a lot of the same circles that I do, but who has a very different kind of hands-on perspective on where fashion and technology met in 2025 and where they’re maybe on converging or diverging tracks for 2026. And that’s Matthew Drinkwater.
For the small number of listeners who don’t already know him, Matthew is the Director of the Fashion Innovation Agency at the London College of Fashion. I’ve never done a very good job of actually describing his job, but I do know that applying emerging technology to the creative industries, fashion especially, is the crux of it.
Matthew also travels the world a lot under that banner, speaking at events and working on innovation projects, so our paths do cross a fair bit in person, but I collared him remotely for the first time in many years actually, just before we both left for the holidays and I got him to join me on a bit of a year-end benchmarking and start-of-year prediction exercise. Needless to say, AI comes up a lot in this conversation, but there’s also a lot more on our slate as well. So let’s get started.
NB. The transcript below has been lightly edited.
Matthew Drinkwater, welcome to The Interline Podcast.
Hi Ben, thanks for having me.
No, no, it’s a pleasure – an overdue pleasure. I think the last time I interviewed you would have been 2020 or something like that. It’s been a good five years.
Ridiculously overdue. Good lord, let’s not dip back into 2020 memories.
No, we’re not going that far back for this one, don’t worry. We are looking back at 2025 and forwards at 2026, but that is the extent of our remit. We’re not trying to analyse anything back in the darker days of the pandemic, and we’re not trying to cast our minds too far forward to where we look silly in retrospect either. I’m trying to strike a good balance between those things. You and I have been on the same event agendas a couple of times this year, so I have a good idea that your answer is going to be, “I’ve been traveling a lot”, but in brief, how was 2025 for you?
Oh, I’ve been traveling a lot [laughs]. Yeah, 2025, it’s been a really interesting year. There has been a ton of travel, it’s been amazing to get out and see in a quite unexpected way. When I started the year, my assumption was that I wouldn’t be doing as much as I have, but I’ve been taken all over the world to talk through our work in AI and immersive. And I think, as I reflect on the year a little bit, it’s been kind of this realisation that something is coming and it feels like, from a fashion perspective, there’s been growing interest over the many years that we’ve been doing this in what technology can do for the industry. But I think kind of this stark awareness that something more significant is happening seemed to be landing a little bit.
I would echo that, think, without fully opening our books, although I’ve done it before for our web traffic and things. We have more readers than ever. As a technology publication for fashion, I take that as a testament to the fact that more people are interested in technology for fashion than they have been before. And we can get into what the shape of some of that interest and demand and stuff looks like as we go. But I can draw a line under that. I can say that I think the depth of interest in the fashion industry, in technology, is deeper than it has been, but the breadth is there as well. And I think that’s probably a recognition of the diversity and the spread of different job roles that are either directly involved in technology initiatives or feel like they will be impacted by the steady march of tech.
I think this is probably getting back to that underlying definition of what general purpose technologies are doing. And you kind of feel like there is something happening which is going to impact every single role across the industry. So, you know, as much resistance as there will always be within the industry, I think there is growing recognition that skill sets and know-all of the experiments and exposure to technology just need to increase.
Yep, I would agree with that. To that point, then, with the Fashion Innovation Agency acting as a kind of conduit between what’s happening in the industry and then the bleeding edge of emerging technology and the talent behind it, how would you sum up the way the industry’s thinking about innovation as we head into 2026? Because I can give you my own glib little take, which would be something along the lines of the spirit’s willing but the wallet is light or empty i.e. there’s a lot of vision for projects but not a lot of backing for projects necessarily. I’m going to guess you might have a more nuanced take though so I’m keen to hear it.
I mean, there’s probably a serious element to that glib take, Ben. I think that the fashion industry has always struggled with where a budget’s coming from to begin to fund shifts in technology or experiments around technology, that for so long, they’ve kind of sat within marketing departments. But I think, to my earlier point of something bigger happening, there is this growing recognition that structures are going to change and the way that innovation for so long has sat within individual innovation teams within businesses or kind of within larger holding companies where you’ll see innovation teams beginning to look at startups and proof of concepts – but how do they force them into houses and begin to affect change.
I think there is this kind of recognition that things are changing but I also would say from a technology perspective, when I look at big tech and its eyes suddenly very focused on the fashion industry again, in a way that felt very kind of ‘2015 wearables-esque’ in its viewpoint, this shift again of where things are happening. And, I think there is this opportunity for those businesses to begin to work together and for us particularly as a team which has deep technical skills but also a deep knowledge of the fashion industry to be that bridge and to help further along that adoption. To just help both technology understand where fashion is at and for fashion to begin to build on the skill sets that clearly need to come through. And as I look at, I guess, the grassroots level for where so many students are experimenting across artificial intelligence and immersive that you see kind of another influx of talent going into the industry or being welcomed into the industry that effectively will begin to force change.
So I think there’s recognition at very senior levels where people want to do stuff. They want to see: what’s my AI strategy. But yet the realisation of that is like individual teams beginning to understand what technologies can be deployed and how best to do them for their individual department, individual group. All of those things are beginning to happen, which I think is, you know, where we might begin to see some significant impact in the year ahead.
What we’re talking about here is kind of twofold. You’ve got the big tech stuff that you mentioned, and absolutely it seems like those industries in particular are coming closer together when we think about the fact that the near future of big tech seems to be reliant on putting sensors and things on and around people’s bodies in order to unlock what people seem to think is the next wave of personal computing at the very least makes a lot of sense that big technology is moving closer to people who, and companies that, have the brand cache and the experience to design those products and make them desirable and useful. So I understand that side of things.
Then I think there’s the more sort of fashion-specific technology sector. So, your companies who create software-hardware solutions which are either explicitly targeting the fashion industry or that target the fashion industry as one of a few verticals. How successfully do you think that sector – so what you and I would really class as like the fashion tech sector – is calibrating its products and platforms for what the industry actually needs at the minute? Because we go back and forth on this a lot because you have kind of a push and pull between these periods where industry demand is ahead of technology fulfillment. And then there’s the opposite where technology pulls ahead and there are periods where the industry then needs to figure out how to map that to their own challenges.
Where do think we are on that journey right now?
So it’s a super interesting question because I think when you look at the big tech side and to your earlier point, those conversations are happening, kind of the elements of design of where sensors and wearables might be around your body. These conversations are actually happening with people in the fashion industry at a very close level. So that, at a higher level, gives me some hope and optimism for what might be coming down the line on that side.
But your question around the fashion tech element, I think those businesses have always targeted the industry in a way which felt like they were creating products that were useful. It just is that same issue that faces any startup of who to talk to, who manages this, what is the impact on organisations? And I think that this kind of restructuring of where decision making sits within fashion businesses of any size and scale is where the wider artificial intelligence question is going to start playing a much bigger role because there’s this realisation that everyone within those businesses has kind of critical data points.
But who are they being served up to and who’s going to start making decisions around this? So whether or not that’s engaging with an SME and the platform that they might be creating, or whether it’s beginning to use multiple data points that already sit across your business. It’s like, what is the internal platform that’s going to be created that serves up the most opportunity and benefit for those industries? And, look, I admire anyone who’s on the SME front, startups beginning to try and sell their product into the fashion industry because it’s enormously challenging. But I guess that I get that sense like no one wants another platform.
The thing is, when you’ve got design teams working on one thing and visual merchandising and merchandising and buyers on another, ultimately you begin to see that singular interface that we’re becoming more used to and whether that’s a text interface and, wherever you are in the business, being able to prompt across that feels like it is a direction of travel and how SMEs and startups begin to pivot to create product – which feels relevant to what’s happening more generally in society rather than something which is specific to the fashion industry I think is the critical point for their success in the year ahead.
I think that’s a good answer. Extrapolating from those two things, so we’ve just talked about where industry attitudes are, we’ve talked a little bit about how well the fashion technology sector is calibrating for those. The gap in the middle there, where you’re talking about mapping technology to that demand, that’s where you play, that’s where a lot of the Fashion Innovation Agency’s work happens because I know you work on a lot of knowledge transfer partnerships, KTPs, which they’re driven by new theses, new ideas from academia and also by marrying those with unmet needs in industry. If I’ve understood KTPs correctly. I’ve never worked on one but I have worked around people who do.
Without giving anything away or breaching any NDAs about what you’re working on, what does that space look like now? Because if you’re in that middle and you are between the research frontier and then the industry demand, and you’re trying to draw parallels between those to create those productive sort of projects that actually advance adoption. What’s happening there? What do those projects look like?
So, knowledge transfer partnerships (KTPs) represent this incredible opportunity for industry to engage with teams like myself and academia because of a relatively low buy-in, you’re able to expand a team to work specifically on an issue that might be challenging for your business. And we’ve done a lot of those KTPs with artificial intelligence companies that have allowed us to kind of build up our own experiments and product development.
So I think of some of the virtual trial and product that we did in 2024 and the sketch-to-animation that we did at the end of 2023 were something called an accelerated knowledge transfer project. But as we were developing those, kind of the real obvious opportunity that jumped out at us is we could be doing this specifically for fashion businesses who don’t have the capability, capacity or really the likelihood of being able to employ an AI team. So where are those skill set gaps and they’re massive across the fashion industry and across whatever – whether it’s design, creation, marketing – there are opportunities to begin to build out projects that are a level of quality that effectively for a relatively small buy-in getting you a PhD qualified research team to deliver something of immediate impact to your business.
And I think it’s really been a revelation. We started doing a lot of work with the slightly smaller parts, the accelerated knowledge transfers, and they’re just such an easy win for industry to come in and say, we need some help across generative AI and image creation or video creation or wherever we get to next week with the latest tools. And we can scale up a team specifically to an individual issue or problem within that business. It’s something which I think weirdly just isn’t spoken about as much. But I think sometimes they’re just engulfed in terminology which feels far too academic when the reality of this is, would you want a really incredibly valuable team added to your business for the space of a year and I mean they take a bit of time to set up but the success rate of those awards is something like 90% because you effectively work within the UK to build up the problem to make sure you’ve got the right people delivering the right thing for that business.
So those things seem like, where are the challenges that people are facing? Can we help build up a team that allows us to scale? We’ll go find the relevant skill sets and we will deliver something. And I think for us at LCF, because of our technology infrastructure, which is, I mean, really second to none, there’s nowhere in the world that has the kind of facilities that we have. That’s an incredible opportunity.
Hopefully there’ll be a lot more of that in the year.
So I think you’ve said it a lot already: AI.
I’m going to ask you, that could just be your answer to this question. Just a simple two letter answer, but I’m to ask it anyway. What technology do you think has defined 2025? Is it AI?
It is, but I think as the year has gone on, and I think for the team and I, the phrase that we’ve started to use a lot more is convergence. And of course, all of this is empowered by what artificial intelligence is doing, but I think it’s creating opportunities across, predominantly for us, our work in immersive technologies.
And so what 2026 looks like is obviously AI heavy, but it’s going to allow us to do things that we couldn’t do before in immersive. So we’ll be doing a lot of spatial work, beginning to look at where Gaussian Splatting and virtual production and artificial intelligence all come together. And anecdotally from the team working together in the office, you can see collaboratively between those who are kind of hard on AI and then the others who are hard on kind of their 3D and immersive beginning to look to each other and going, I’m struggling with this. Maybe what you’re doing and what I’m doing might come together a little bit. And I think those sort of elements of where the technologies are coming together to enable us to do things. Our reskinning reality projects with our research into volumetric capture wouldn’t have been possible without a few developments in some AI models that helped us to do things that were proving difficult.
And so, yes, yes, it’s been AI, but I think more importantly, it’s what AI is doing to all of the other work that we’re delivering.
Yeah, I think that’s a really interesting way to look at it. Just before we go too much further for anybody who might be sitting listening to this and thinking, he said immersive a bunch of times, what does he mean by immersive? What do you mean by immersive?
So this will be our work in mixed reality, augmented reality, virtual reality, and I’ll stick virtual production into that as well because that’s an area of work for us too. So yeah, that is where I would define immersive.
It’s a good definition. I didn’t want us to get to the end of this episode and then have me realise that we haven’t defined one of the key things that we ended up talking about. So on the AI side of things then, back in the late spring / early summer of this year, our AI report for 2025, we ended up framing AI adoption and diffusion as being kind of reaching a point where it’s transitioning from being a lot of open-ended, kind of wooly definition experiments and possibilities to more discrete applications with clearer kind of success criteria, fail states, ROI objectives and stuff like that. Or to put it another way, less of AI as a nebulous idea and more of AI as software. I’m guessing based on what you just said that you see AI as additive and maybe transformational to a lot of other areas that you’re going to agree with that take? Feel free to not though.
And tied to that, what do you think of as being the viable revenue generating deployments of AI right now? What is it that’s actually on the ground working, implemented, where people can point to it and say there’s an application of AI either standalone or as additive to something else I was doing and it is delivering a return for me? And is there anything else that’s just around the corner or just about to hit that level of maturity?
I’d like to be talking to the teams who are kind of using something generative that is delivering kind of specific KPIs and ROIs. I think I would define this in two different areas and the kind of generative models for image and video creation, which you see lots of experimentation with virtual try-on and kind of marketing campaigns. Kind of AI as an artistic expression as being that one area where there’s been, I would say, the majority of work done by the industry. And those still seem very, very experimental.
And I think also there’s a huge degree of caution and nervousness about the use of those particular examples within the industry because they bring up questions about, should you be using a real model? Should you be using a real photographer? All of those things. And I think in many ways that’s held back a lot of the experimentation in other areas. I mean, clearly across merchandising buying there are really big opportunities and there are some fairly well defined startups in that space that are delivering return on investment for businesses in that area. But do I think they’re really mature? I’m not sure I would say that they are. And it still feels to me that that actual use case where business teams, whether or not they’re using ChatGPT and Perplexity and Notion or whatever it might be within their marketing teams to deliver efficiency impacts, I haven’t seen anybody talking about that. I mean, I’ve seen some really good presentations from design teams, how they’re beginning to help their design teams utilize generative tools in a way which is empowering them away from kind of traditional 3D design, which was always a kind of much harder sell into design teams. You can begin to see that, but yeah, that’s kind of where I’d be on that.
Yeah, I hadn’t really crystallised the thinking that way, but the readiest use cases for AI, generative AI if we think about the ones you mentioned, which is replacements for photography, i.e. the thing where the technology is perhaps best positioned to do it and where there is, as a business case, because you have an expensive time-consuming activity that you can replace with a cheap, relatively turnkey activity. It’s weird that the readiest deployments are also the most sensitive ones, culturally.
Exactly. Everyone you talk to, there is awareness of that opportunity, but I know very, very few kind of larger scale businesses that are looking at that as an immediate deployment opportunity, because I think they’re too concerned about the impact and perhaps the pushback from the industry at large.
Yeah, and I actually want to get into the cultural stuff around AI in two ways now.
So let’s start with how it’s being received by that creative community you just mentioned. From my perspective, I think that’s a frontier that’s moved a lot more quickly than I’d expected. I’ll be candid. When the first AI Fashion Week launched, which I think was in 2023, it felt tone deaf to me. That’s the most diplomatic way I can put it. When we have the output of fledgling generative models, and we’re going to instantly elevate that to the same status that fated designers have to earn. To me, and again this is a very personal opinion, that read more like devaluing the work of design rather than opening doors to under-platformed people and allowing them to get into design.
I still don’t think that time has been super kind to the idea of an AI fashion week but to your point I do 100% recognise and hear that the working design community within brands has actually really taken to AI in a way that I wouldn’t have expected based on that initial sentiment that I had.
So if you read our 2026 DPC Report, it’s very clear that there are overstretched under-resourced design teams that are looking at generative models as genuinely viable creative partners. So it feels like, from that cultural point of view, there’s maybe a disconnect between the loudest voices – your independent artists, design community, and commentators like me, where a lot of people have skepticism, resentment around A – and the realities of work where people have too many jobs to do, and they need tools to help them do it, and they’ve actually taken AI in stride.
You’ve done a bunch of hands-on work with AI. You also go to more physical Fashion Weeks and things than me. Let’s just say a little bit more about that cultural reception of generative AI from a design point of view within industry, because it’s in a different place to where I would have expected it to be at the beginning of the year.
Yeah, it’s an interesting point and I’ll push back a little bit on that viewpoint on AI Fashion Week because I was on the judging panel for the couple of times that they’ve done it. So I actually got to see a lot of the submissions from AI Fashion Week and to have a closer relationship with the winners that came through and actually very few people from more of a traditional background were utilising those tools back in 2023. And it actually did represent this really amazing moment, from everything that I saw, of people that I never expected to be within the fashion industry. And not all of the imagery reflected the kind of quality that you would imagine. But actually the winners have gone on to build their own careers and some of them are on the west coast of the US working in AI companies and building their own AI agencies and delivering really beautiful work. And I think they wouldn’t have had that opportunity had that not been there.
And for me, you know, the industry is closed. It’s difficult to get into and it’s expensive. And these tools, particularly in ‘23, if you know those people who are early on to it and started working with them and embracing the opportunity, built opportunities for themselves that simply wouldn’t have existed. I mean, of course there are things that could always be done better, but in no sense did I get back then that it was in any way a threat to physical Fashion Week, nor should anyone imagine that it is to this point.
I find that conversation really, really interesting because they’re clearly separate things. As to where we’ve got to, I mean I think you know that I sit on the technical working group for the UK government on AI and copyright and it has been a very, very emotional ride over the last 18 months or so as those conversations have evolved and, I don’t really have a clear view as to where this ends up, but I guess my broader feeling is that the technology is here and creatives simply do not need to be afraid of it. There’s been a constant message that genuinely if you work within the creative industries, I don’t think you need to fear pattern matching algorithms that produce kind of the average of what most people would do. And almost every example where you see a wave of adoption of AI tools is people doing the same thing as everybody else.
Definitely. I would agree with that. And I think just to clarify my bit, I don’t think I saw AI Fashion Week as a threat to physical Fashion Week; I think I saw it more as putting relatively non-skilled attempts at something right up with skilled attempts at something, i.e. places where people have spent a lot of time honing craft versus places where those people might rightly think somebody’s taken a shortcut to my craft.
However, your point is an interesting one, which is that you have to be invited in the doors to have the opportunity to hone your craft. You have to actually get in there to begin with to be able to develop yourself and develop your skills. If opportunities like this and tools like that give people that leg up to then be able to go and either distinguish themselves if they have the talent and the capabilities to do it, or I guess disappear into that morass of sameness if they don’t have the talent to do it. That’s probably the right outcome.
And I think to that point, this is where we’re at with the technology that people worry a lot about ‘AI slop’ and it’s a term that has just kind of come into the vernacular over the past 12 months we haven’t yet defined what that hierarchy of skills are yet around the technology and everybody wants to see things of incredible technical quality. When you go to the movies you want to see good CG and you can very quickly tell the difference between what’s really good and what isn’t to a point where it kind of fades into the background and you don’t think about it. And ultimately that’s where this technology has to go, and it feels like we had similar conversations about the early adoption of 3D and digital fashion in those days of being able to define who are those who have that level of artistry to actually move people.
Yeah, I think that’s a good way of looking at it. And if I could do an analyst summary, it would be putting technologies in people’s hands eventually. There’s a lot of hand-wringing in the initial stage, and some of that hand-wringing is probably justified. Eventually, quality market and the output market determines what survives and what doesn’t. Eventually, that’s where the judging is done.
And I think, to that point, am I, as somebody who writes and publishes, mad that the average standard of writing, the average floor, the average baseline could rise as a result of AI? Definitely not. I think it’d be wonderful to be surrounded by an average standard of writing that was better. Do I think that giving people tools to help them write is a bad thing? Also not. There are plenty of people with great ideas who don’t have the experience to express them. Do I think that people will still be able to stand out based on how they use those tools and how they use their own individual talent? Also, yes. I think that’s still the market. And we’re pretty firm believers in that: that if you continue to produce quality work and all boats are rising around you, quality work still stands out. And I think that’s true across a lot of different disciplines.
Yeah, I’m not gonna disagree with that because ultimately you can largely tell when you begin to see things out. And I think we’ve both had those conversations where it becomes very obvious. And I think this is the kind of teething issue around many of those technologies – where do we find a place to fit in within whatever creative pipeline you have to begin to allow you to do what you couldn’t do before, or where you have that talent, you can begin to differentiate.
And we see it at the university. There’s marketing students who get challenged to deliver campaigns both with AI and without AI. And for those from a creative background, you see that very obviously in the kind of non-AI stuff, but maybe it’s those who struggle with that but might have great ideas of how to write something and are then given a tool to kind of level that playing field. But in many ways, it’s not really about leveling. If you’re an incredible creative, you’re going to find a way to utilise those tools to do something that people find unexpected and amazing.
Yeah, and if you didn’t have access to the resources and the opportunities to properly exercise that before and the generative models or other tools give you that uplift, then that’s an ambiguously good thing.
One tiny extra question: I think we’ve covered a lot of it, but it’s about consumer attitudes, not just of AI content, but digital content in general. So you and I both have kids, and I don’t know if you see this, but two of my kids are old enough now to have opinions about content that gets pitched at them. And I’ve noticed over the last year in particular, their shorthand for anything that looks or sounds inauthentic or bad, i.e. you mentioned CG, so bad CG in TV and films, overly formulaic pop music or something, they will say “that’s so AI”. This has completely taken me aback. I was not expecting that at the start of the year whatsoever.
And to be clear, neither of them are old enough to have any idea about the actual tools involved in generating or authoring 2D or 3D media. But it does feel to me like looking at them and their friends, we’re looking at a generation of people where there’s a broad pushback against things that don’t feel real. But what’s weird to me, that’s also happening at the same time when the quality bar for what talented people can generate digitally, whether it’s using AI or 3D modeling or performance capture or what have you, is higher than ever. So we can create much, much better, much higher quality, much higher fidelity, non-real content than we’ve ever been able to. But there’s also this sentiment that people don’t want what isn’t real. And I don’t quite how to think about that. It’s taken me by surprise and I’m wondering if you’ve seen anything like it.
So I haven’t had that phrase used in my house from my teenage daughters, but I kind of love that they are using it because I think it begins to bring into question the thing that everybody talks about with these tools – critical thinking, beginning to question what’s in front of you. And it’s one of those areas which I think clearly there’s a generation that is going to need that kind of thinking. In many ways, haven’t we always had to begin to define between what we find – whether it’s real or not is not the point, it’s kind of the quality of what’s being created. So, I think those questions are going to circle whilst people find it very easy. And in many ways, what’s happening is that, kind of, if you imagine the internet as being that place where suddenly we could all publish stuff, regardless of the quality, everybody had that outlet to publish stuff. And now we’ve got the tools and the infrastructure to allow us to create anything. And so I think invariably that does mean that there is this tidal wave of stuff that could be coming down the line. And where and how we choose to navigate that, how do we begin.
It’s going to create some amazing opportunities. But I think how we find and navigate our way through that and begin to identify the elements of which ultimately for any creative industry has to provoke some kind of reaction to it. Like whether it’s “so AI” or what is the polar opposite of that, create something which people feel really valuable, I think is where we’re going to have to land on.
Yeah. And I think what’s interesting as well is it used to be the case that you would see an amazing piece of art. So it could be painting, could be writing, but for our purposes, let’s stick it to the FX 3D immersive, that whole space. It’s your person of my sort of age who watched Jurassic Park and instantly wanted to understand how it was done. That initial spark I think is behind the journey that people go on to acquire their own skills by downloading open source tools like Blender for instance and playing around with that and then people saying I want to go and work in VFX or I want to go and work in games. I want to go and work in the 3D side of fashion and I’m going to go into institutional education to do that.
Do you think that inspiration spark, that sort of pipeline is still running smoothly for fashion? Are people still going to see that kind of work out there and say, I want to know how that was put together and I have the tools and I have the time to go figure it out because the reason that I think I’m concerned about this is I’m thinking about AI specifically as a bit of a black box when it comes to how was this done at least to some extent. And maybe as a skill compressor like we’ve talked about – kind of driving down skill ceilings and driving up skill floors.
I just wonder, for people who look at great content now, do they feel the same way? Do they feel like they could go and figure out and unpick and experiment with and then do their own versions of that? Or are we careening towards a place where people create great content and then that great content just becomes the next cycle of sameness until somebody else figures out how to stand out from that?
Or have I just described culture in general and actually I’m worrying about nothing here?
These are massive questions about the future of education. And, you know, obviously this is something which is being discussed at the university because you can. I remember when the internet cropped up and of course everyone was saying, well, who needs to learn? And you’ve got it all at your fingertips. And yet this time around, I guess it’s the same kind of conversation, but the speed and scale of which you can deliver feels a little bit different.
But specific to fashion, the creation of physical product still requires an element of infrastructure around it. And so when I give tours around the building, if I start up on the 13th floor and walk down, you go through three or four levels of kind of just hard machinery. And this is not where artificial intelligence is going to impact. One of the questions we were asked before we moved into our new building in East London a couple of years ago was, certainly when we were in the design phase of the building, we got asked the question of what does fashion education look like 100 years from now? And our only reference point is what fashion education looked like 100 years ago when London College of Fashion started. And we have lots of those images. And surprise, surprise, it’s lots of sewing machines. And as I look at those photos and then I look at the building now, albeit we’re in the most extraordinary building, it still kind of looks the same.
Yes, these technologies drip in and become part of, you know, where we’re using. We have 3D printing, we have our big studio lab, and lots of compute power throughout the building, but still at the core of what we’re delivering is something so physical and tangible. I feel like that pipeline that is coming into the university and the numbers would still support that are still really healthy.
I think on the fashion business element and the media and communication side, these are things which could face some challenges but I guess ultimately I go back to if you’re an undergraduate or postgraduate, what are you coming to university for? Is it to just learn a specific skill set or is it that kind of opportunity for you to be immersed in a culture and a way of thinking around an industry and the connections that that builds up?
And I think the value of that is still going to be so unbelievably important that you have that time to begin to be in a place where you have all of those different elements around you – from technology infrastructure to kind of traditional heritage and craft – that is your place to learn.
And so I still remain incredibly optimistic about the pipeline and where the role of universities and education sits in an era of AI. Because I think that critical thinking and depth of knowledge of an industry is so incredibly critical to who you’re going to be as an individual. I still remain robustly confident of that direction of travel.
So ‘immersive’ and ‘immersion’ are probably two operative words for this one. And again, I would agree with you on that. I think, as somebody who I did not come from inside the fashion industry, I’ve been in it for 16 years now, but my background is not there. The immersion part of it has been far more instructive about how I think about things and who I am and the position that I have today than the actual technology understanding or the ability to write or speak or what have you. Just time in industry and time around people who are, a lot of them smarter than me and a lot of them smarter than anybody else who’s coming in, who spend their lives thinking about how to address challenges. And yes, you might be bringing new tools to the table. The mindset is the most valuable thing when it comes to applying those.
Okay, let’s end with a few minutes that we have on some 2026 predictions and let’s start with the optimistic ones. Am I going to hold us to account on this time next year? I don’t know. Let’s see. I’m going to take a read on it next December and see how well I did and then we’ll see. But if we cast our minds forward and we picture ourselves sitting here again at the end of 2026 or early 2027, what, from the current selection of topics that are top of mind for you or for the wider industry, do you think we’re still going to be talking about in a positive light?
My goodness, it’s hard to imagine where we’ll be in the generative field a year from now. But do I think that I’ll still be talking about it optimistically? Yeah, I feel like we will be. But my earlier point of convergence is like, what is the technology doing to open up opportunities around wearables, immersive technology, all of the things which kind of allow me and my team to build experiences more realistically in a way that we couldn’t do before.
And I think when I look at what we’re planning to do in the next 12 months, when I reflect back on the projects that we will have delivered over the next 12 months, will I feel like we’ve made really big strides forward? Yeah, I think so. So for me, it will be that convergence of technologies. When we look at spatial experiences, world models, that ability for us to kind of place people into ever more realistic 3D environments, that’s where we’re going to be sitting over the next 12 months. And I think all of the tools that crop up around us to enable us to do that are going to feel very, very empowering.
Okay, then conversely, where do you think the wind might drop out of the sails? What’s something that seems either super important right now or something that we’re told is just destined to always be around that might actually end up being de-emphasised if we were to do this again this time next year?
Okay, it’s interesting. Are we in a bubble? I don’t know. It kind of feels particularly around fashion that we’re still at that very early stage of AI adoption. From a pure tech perspective, it’s hard to see where the continued value of pumping enormous amounts of capital into developing large language models that are superseded a week later by somebody else. Whether or not that business model is viable in any means, shape or form, that is a very serious question. If something was to fall out of the market in that respect, that might leave us all questioning how quickly and how fast we thought those tools might be adopted and integrated.
I don’t know. I think: is this a general purpose technology? Is this something that is going to impact everybody in the industry in whatever role you’re in? I feel like it is. So I’m not sure whether the wind will be taken out of the sails in 2026.
Do you think on that basis that it is a general purpose technology that affects everybody? Do you think it gets to that effect by being productised for individual disciplines and job roles?
Yeah, I think it likely does. And this is kind of that big question around bundling and unbundling. I think there’s always been this hope of being this one singular interface. But I think realistically, those very specific use cases for individual teams across the industry feels like the most viable opportunity.
So, yeah, how that gets delivered and how teams begin to integrate that into organisations, I think maybe where the challenges exist around that and what kind of infrastructural changes that might require for the industry is where the pace of that adoption might be slower than people might hope. But I think that’s the likely outcome.
Yeah, and I would also say I think I’m of the same mind and I think also the opinion that even if the bottom falls out of the big LLM market on this – which is predicated on the assumption that everybody’s pursuing a generalised super intelligence and that’s what’s necessary – I think even if that were to happen, based on the technologies available to us now, both commercialised and open source, it still feels like there’s so much runway to do that productisation. It feels like we’re very early on that journey.
Yeah, 100%.
Okay, well, let’s revisit this in 12 months and let’s see. Let’s see how we did. I will hold us both to account and we’ll judge it from there.
Matthew, thank you so much for coming on. I really appreciated this conversation. I always enjoy talking to you. And, like I said, having been five, nearly six years since I last interviewed you definitely feels like too long. So I hope we get to do this again in the future.
Yeah, that’d be great. Thanks so much for having me.
Not at all. It’s been a pleasure.
That’s the end of my chat with Matthew. Now, as you can tell, he and I agree on a lot, not everything. So it’s going to be interesting to see how 2026 develops. On that point, this is going to be our sixth year of The Interline, which given the state of the media industry at the moment is a victory by itself. And we have readers and listeners like you to thank. I’m not asking you as a listener or reader for anything in return besides keep reading and keep listening. And I’m confident that in exchange for that, we’ll be able to keep putting out things that you want to read and things that you want to hear.
This is also the point at which we want to open up listener questions for the show now that we’re in 2026. We’ll aim to answer one at the end of every episode, either ourselves or in partnership with one of our guests. So if there’s something on your mind, then you can email me directly at editor@theinterline.com and we’ll put your questions into the mix. Hopefully we get a chance to get to all of them over the next few months.
Now, as somebody with a young baby and two older kids, this time of year also puts me in a bit of a sentimental mood that you might not find me in any other time of the year. So I’m going to strike while the iron’s hot. I sincerely wish you, as a listener, as a reader, as a person, every happiness and success for the rest of 2026. And I’ll speak to you again soon.