The Edit is our new weekly show, where Social Editor Grace Robinson quizzes Editor-in-chief Ben Hanson on five of the most significant fashion and technology stories from the past seven days.
This first edition covers AI-powered virtual try-on in resale, warehouse automation and jobs, an AI-likeness lawsuit, the darker side of livestream shopping and agentic commerce, and Amazon’s investment play for a different kind of AI-native personalisation.
This show is available in video format, embedded above, as well as audio, on Apple Podcasts and Spotify.
For existing audio listeners of The Interline Podcast, our prestige interview show will now release on Thursdays, and will be upgraded to video soon. Subscribers to our mailing list will receive notifications for both shows.
NB. The transcript below has been lightly edited.
Grace Robinson: Welcome to The Edit from The Interline, a new show where we run quickfire analysis on our pick of the most important fashion and beauty technology stories from the last seven days. I’m Grace, the Social Editor, and I’m joined by Ben, Editor-in-chief.
But before we do that, I want to ask Ben to introduce the show since this is our first episode.
Ben Hanson: Hey, Grace. Good to be here. Thanks for teeing this up. Because this is the first one, it’s going to be aired slightly longer than our future editions. Just as an FYI, you’re not going to have this intro from me every time. This is just to introduce a new format to our listeners.
Well, anyone who listens to The Interline Podcast as it exists today is familiar with it as a forty-five-minute to sixty-minute deep-dive interview show where I pick a single guest and I talk to them about a very specific topic at length and in-depth. That’s great. Those are going to continue. They are absolutely not going anywhere.
But what I want to do with this and what you and I are aiming to accomplish week over week is to provide more of The Interline’s perspective on the wider news and everything that’s happening currently. The interview shows are a great way for us to take a particular topic and really wrestle with it. These shows are intended to be much more of a finger in the air test, what’s happening this week and what do we think it means, what are the implications from a fashion technology point of view.
The format here is also going to be very different. So instead of me interviewing anybody, it’s you interviewing me. So, you’re going to be asking me questions about headlines and things that have surfaced from your research, our research over the course of the last seven days or so. And the format for this show is that it’s intended to be shorter, digestible, and an easier listen. You’re essentially dropping in on the kinds of conversations we have at The Interline regularly anyway.
So, these shows are going to be more in the 20-25 minute range. We’re going to get a little bit more specific about how that works over time, and I think we’ll get a bit more refined on the format. But these are intended to be shorter listens, easier listens, and more expansive and broader listens.
So, each week, you’ll come to me with five or so technology and fashion and fashion technology stories from in the last seven days. We’ll talk about them. We have probably 2-3 minutes for each story that you and I will share, and we will present our perspectives, and then we’ll just move on. Now all of these headlines come from our own research, from research we found elsewhere, from reporting we’ve seen elsewhere.
We also want to encourage people listening to the show to send in tips and ideas and headlines and things that they would like us to talk about as well to help close that loop.
That’s the very longish intro for this format, and you’re not going to have that in the future, so every week from now on we’ll get straight into it. And Grace, I’m going to ask you to do that now, hit me.
DressX × Depop — virtual try-on comes to resale
Grace Robinson: The first question and the first story that I wanted to talk about was a story between DressX and Depop. So, for those who don’t know, DressX is a digital fashion platform, but it really got its start in COVID, but now it’s moving into more AI powered virtual try on.
So Depop did an event and DressX set up an AR try-on AI powered mirror. Users or visitors at the event could try on different digitised versions of Depop product and then once they’d created a look, they could actually get a link via email or text and then they would go on to Depop and they could buy the physical product.
I found this story really interesting because it obviously showcases a more valuable use case for digital fashion but beyond that, Ben, I was really interested to know, do you think this AI-powered virtual try-on experience is going to help fashion resale and beyond that, do you think this user-generated AI content will become a big thing in e commerce generally?
Ben Hanson: So, two things, I have a bugbear about the term digital fashion. We’ll put that to one side, and we can pick that up at some point in the future. So, what you’re describing here is that Depop is a secondary-market marketplace, and DressX has traditionally applied their AI virtual try-on to firsthand sale. Most, if not all, try-on has been applied to firsthand sale.
Virtual try-on is having a bit of a moment at the minute. We’ve previously referred to it as fashion’s poisoned chalice from a technology point of view because so many people tried VTO over the years with different technology underpinnings, and it hasn’t seen broad adoption. It feels like AI is changing the game a little bit there for firsthand sale at least. Now the secondary market has a trust and experience delta when it comes to the way that it feels to interact with that versus interacting with a firsthand sale. Traditionally, you buy something new, yes, you’re getting a new product and you’re getting a guarantee of quality and condition and experience and everything else from that. The new product experience is also where you typically have the cool experiences. That’s where retailers and brands invest.
So, if you’re going to get virtual try-on, you’re usually going to get it in the firsthand market. So, this is especially interesting because it brings it to the secondary market. And I think if it closes that experience delta so that people get a cool, fun, engaging way of shopping for preloved items, then it encourages more people to buy used. So that’s encouraging from that point of view.
Technically, this one’s really interesting because I think the standard of photography that people create when they’re selling second-hand goods is a lot lower than the staged and studio shot photography that you get for firsthand. Now from an AI VTO point of view, if you’re ingesting really good quality lay flat and mannequin and studio images and things from firsthand, then you have an easier uplift than you have from more candid smartphone shots, less staged and less codified photography in the second-hand market. Technically, I’m really keen to see how this works.
Now as I understand it, it’s a ‘go away, come back to you via message and email’ thing. I don’t know what the time lag is in that, but for me, this is fascinating because it changes a little bit the way that people shop second-hand, and it’s also an interesting technology problem that I really want to see how they solved it.
Warehouse automation — robots, jobs, and Asda versus Amazon
Grace Robinson: So, the next question is a bit more behind the scenes, and I want to ask you what on earth is going on with warehouse automation? And I say that because I’ve seen two really conflicting stories this week. The first one was from ITV News, and it was talking about ASDA’s clothing line, George. And basically, right now there are three warehouses for ASDA’s clothing line but they’re going to be reducing that to just one and in that process they’re also going to be cutting a thousand jobs of people who work in these warehouses. ASDA reported that this is because they’re introducing these new robots, so redline robots.
On the flip side, I saw a very contradicting story from Amazon who are introducing their new AI powered Proteus robots and they’re saying that these AI powered robots can actually do the more manual work, therefore it opens up new job opportunities for higher-skilled and more creative work.
These are obviously two very contradicting stories, like I said, and I’m just really interested to know what should we think about robots for automation? Are they going to create jobs? Are they going to reduce them? What’s going on?
Ben Hanson: Sure. I think specifically the statistics, so you mentioned George at Asda are saying they’ll cut jobs by about a thousand. I think Amazon is saying that they will create something like 25,000. It’s multiple tens of thousands of jobs.
As always with this thing, there’s some nuance and some extra context.
So for anybody outside The UK, George by Asda isn’t the world’s most popular clothing brand, and I think you have to read these stories with that in the back of your head, which is to say: if you’re consolidating a lot of the operational side of things, it’s probably not because the brand is growing. Then Amazon has precisely the opposite problem, which is that they have a huge amount of demand, a huge amount of volume and a slightly different mandate when it comes to automation. So, you can be automating and optimising and consolidating something because it’s of a fixed size, and you can go, okay, this is my clothing operations, I can see redundancies here, I can see opportunities here to do things this way. Or you can be saying my business is growing. I have a much wider total addressable market than you think, and I need to lean on automation alongside hiring as a way of helping me to scale my business.
Now, most brands in fashion and beauty are not Amazon. Most companies are not Amazon. Most companies are not forever growing and scaling and don’t have the same operational uplift and clout that Amazon has. So, I think automation in general in warehousing is more likely to eliminate jobs than it is to create them. I think the creation is a temporary artifact of Amazon’s growth here.
If you look at groceries, so particularly here in the UK, you look at Ocado as an example, a huge amount of their warehousing is fully roboticised (if that’s a word) and automated. Often when you talk about automation, whether it’s in warehousing or in design or any other function, people will say, it’s not going to eliminate jobs because somebody’s job is to oversee the robots. Like it’s become a funny, fixed cliché, which is we’ll put robots in here, but it’s fine because your job is now to maintain the robots. There is not a one-to-one mapping of that, and it’s also fair to say that not every warehouse worker, just as not every designer, not every pattern engineer, not every supplier coordinator or whatever can or should be retrained to handle the automation side of things.
Broadly speaking, I’m still a bit more radical in my middle age than I thought I would be in the sense that I lean more into the social side of this. You would expect me to be keener on technology automation. If I was in this type of role, I would be expecting to be automated away rather than expecting to have more people working alongside me long term.
AI and likeness — the Francesca Pujos lawsuit
Grace Robinson: The next noteworthy story I saw was about a lawsuit I saw in New York, basically a model called Francesca Pujos did a modelling job for a value-based retailer in Brooklyn called Rainbow USA. She did the modelling work, they had a contract, Within their contract it said that they could do some light editing work to the images but then in March of this year, so 2026, she noticed that the company Rainbow USA was using her likeness to generate new imagery and not only this, the images that they generated were actually very provocative. So just one example is that it showed the model’s likeness sitting on a stool spread legged, so a very provocative pose. Also, they changed her body, they changed her hair but actually her face and likeness were the same, so it looked like she’d done this shoot.
This obviously has so many issues that we could talk about but for me it stood out because it really feels like it’s the tip of the iceberg of different stories like this especially with AI being such a new technology.
My question to you Ben is why do you think a company, a retailer would think that this is okay? And also what can be done to avoid this scenario in the future?
Ben Hanson: Yeah, I love this story. The original, a lot of people cited it from the New York Post article. We pulled the docket from the New York Supreme Court and went through it and specifically analysed it. It is potentially like a bellwether case or at least it’s certainly one of the most publicised, ones in this space. We have an article being written by a former model now technology executive to appear in this year’s AI report, which will be coming out in a few weeks’ time, which gets after precisely this issue.
So, I’m going to roll up some of the findings from the docket and some of his analysis in my answer. I think what’s especially interesting here is that this is not an AI lawsuit that is going after AI companies. Right? I’m going to assume that there was a Gemini model behind this. So, it was either one of the Nano Banana series or it was GPT image 1.5 or 2. No one’s going after OpenAI and no one’s going after Google.
The model in this case, Francesca, is specifically suing the retailer for the way that they are using AI. So that’s an important distinction. This is not about how her face made it into training data. This is not about the fact that a model unprompted and unbidden generated an image that looked like her.
This is a company saying, well, we’ve previously done a shoot with this person. Therefore, we feel either covertly or openly that we have a license to just remix her identity and her likeness. That’s the point at issue. The specific statutes that she’s going after are fairly typical. It’s mainly around licensing and existing structures that exist, and the defamation one is interesting, like taking somebody and putting them in a pose that they wouldn’t have actually volunteered to do themselves.
But the fascinating part is that this is about behaviour on the part of a brand or a retailer. And this is also behaviour that a lot of brands will recognise that they probably do for internal purposes. So, if you have a photoshoot that you already can already rely on, you have reliable models, and you are coming up with a new collection, a generative workspace. It’s going to be very tempting to just say, let’s just bring in that model we shot before as our reference. Let’s use this to generate a bunch of new poses for this that we can use for internal selling or external selling afterwards. Right? That is not how things actually work. That is not how traditional modelling contracts work. That is not how likeness works. That’s not how a whole bunch of things work, but it is very, very common practice.
I think the key part here to rationalise and for people to sit with is the realisation that it’s very easy with the current set of generative workspaces to do work that is supposed to be creative and experimental and for in house purposes, and then to use the same workspaces and the same tools to generate marketing images, to generate eCommerce PDP content. Because that’s how a lot of these workspaces are sold. They are sold on the basis that you do creative experimentation in here, and then you might as well generate your downstream facing assets as well. If you are not super clean about who you are bringing in from a face, body and likeness point of view, before you know it, you slow walk into one of these lawsuits in the very near future.
The dark side of livestream shopping
Grace Robinson: The next piece that came across my desk this week that I found really interesting was on the dark side of livestream shopping. This was actually a Vogue business piece, and I believe it was written by Megan Doyle, who I think’s written for The Interline in the past.
Ben Hanson: Yes, we love Megan, she’s written some great content for us before.
Grace Robinson: Yeah, it was a really, really great piece. Megan goes into the rise of livestream shopping, which was really big in places like China but now it’s becoming really big in the West as well. And these are platforms like Whatnot and Tilt, and she talks about how popular they’ve become but she also goes into the dark side of these platforms, specifically how they employ these manipulative tactics to keep people really addicted and buying things on the applications.
So, these are things like the fast-paced nature of how the streams work, also the gamification of them and all of the fun novel bells and whistles that keep people really addicted to live stream shopping. And I find this really interesting because as a fashion consumer, I can’t imagine buying fashion in this way, but I do know that it is becoming very, very popular.
So, I wanted to know from your take Ben, do you think that we should be concerned about live streaming? Do you think that it’s here to stay or if it is a bit of a fad or a trend?
Ben Hanson: Okay. So, a couple of things. Everybody should go read that story because Megan’s a clear thinker, great writer, and there’s really good reporting in that.
To take your second point first, live streaming is huge. Shopping is gigantic. I’m older than you, so it’s not something that I use, if it’s already not something that you use. However, I attended a fashion show at a big studio here in Manchester a couple of months ago. And as part of that, we had a big studio tour, and they have a very big livestream setup that brands use, brands across fashion cosmetics. In cosmetics specifically, I believe they’ve been the host for some record-breaking streams in terms of attendee figures, in terms of gross merchandise volume and things like that.
If you’re not aware of the scale of live stream shopping and that you don’t interact with it, it can be hard to reconcile with just how huge it is. So, I think this is a really timely piece from that point of view.
So, is it going anywhere? No. Just because I don’t interact with it and you don’t interact with it is absolutely the way that things are. I would also put it next to the AI-mediated shopping experience that people are talking a lot about at the moment and the agentic side of things, because they’re of a piece in two ways. One is that they’re both tech enabled. They can’t exist without it. You can sell traditional ways without technology. You can’t do either of these things without a technology unlock. So, all of the vast infrastructure behind live real time video streaming and interaction is behind the live stream shopping phenomenon, and the development of large language models is behind the AI shopping phenomenon. They’re both unlocked by that thing.
They’re both also potentially pretty problematic from an experience point of view because as Megan points out in that piece, live streaming creates a sense of urgency and scarcity that encourages people to make purchases they wouldn’t do otherwise. If you look at it as just QVC for younger people on the internet, you’re treating it as more benign than I think it actually is because what you have is people are used to instant gratification on these platforms, and instant gratification lends itself to impulse purchasing. If you pair it, as a lot of platforms do with buy now pay later models, you are creating a flywheel for instant debt generation as well for younger people.
The same is true for AI, and we’ve written about it before: it’s a very short hop from personalised shopping interactions through ChatGPT or Claude or Gemini to, prescriptive behaviours.
AI chatbots are very much optimized for engagement and for giving people what they want. It’s not hard to see how that becomes a way of incentivizing purchases and forcing people’s hand there. Again, pair those with Klarna and so on. And before you know it, what we have is a system that really pushes people towards purchase in a way that I suspect might come under regulatory scrutiny in the long run. But livestream shopping — huge, absolutely gigantic.
AI-generated merch — Amazon prints on demand
Grace Robinson: The final story is something that I saw on the Amazon blog this week and it’s to do with AI generated designed merch. I think there’s been a time in everyone’s life where they’ve wanted to create customised merch, whether that’s a t shirt, a hoodie or a water bottle, something like this. Now Amazon’s Alexa for shopping is actually making this even easier because any design that anyone thinks up, they can now generate that design using AI and put it on a t shirt or a hoodie like I said. And not only this but Amazon is now able to create these products on-demand, and I believe they’re also using their Prime eligibility to also ship these products.
On one hand it goes without saying that this service could be so popular, you can see why it would take off so much. On the other hand, people are really not liking AI at the moment, especially young people. So, you could also see that people would really want to rebel against this service and not use it.
What is your take, Ben? Do you think this is going to be really popular? Do you think it’s going to take off? Do you think it’s a good thing or not? Just what do you think about it?
Ben Hanson: So, I won’t pretend to have a good read on how younger people feel about AI in particular, except what is out there as published data, which is not encouraging. Is AI is anathema to what a lot of younger people want in their creative brand expressions and in the way that they are marketed to and story told and engaged with. O
n the other hand, I also think there’s a whole lot of people who are not artists, don’t want to go through the hassle of becoming artists, but do want to creatively express themselves in what they wear. This is something that traditionally you would have had to go through screen printing with minimal order quantities and so on. If you want to make your own t-shirts, you have to find a supplier of high-quality blanks, you have to do the artwork yourself, you have to prep the artwork to be ready for traditional printing methods.
Now Amazon are one of the largest customers of Kornit specifically, but I suspect maybe other digital direct-to-garment printing technology hardware. They’ve been buying that up for a while, they use it in their private-label and white-label product lines for t shirts and hoodies and things and so on.
So, they already have the infrastructure to do this. That is not new. You can do unit of one high quality digital print onto blanks of any quality. Right? And there are whole operations aside from Amazon set up around the UK, the EU and the US that do this. They do effectively drop shipping, where they will also print the artwork onto the t shirt for you. Now as for whether people will actually use this, I suspect that they might because we saw last week that Amazon were adding image generation to their search, where the where somebody was saying, okay. I want a blouse that looks roughly like this. This is the colour that I want. This is the pattern that I want. It would generate fake images of fake products, and then afterwards, it would try and map those to real products. Guess what’s a really good way of ending that transaction? Instead of mapping it to some third-party products that you stock as a marketplace, just encourage people to print their own.
If somebody’s searching and they’re saying, I want a red t-shirt, and I want this on it. I wanted this pattern. It doesn’t have to be artwork. It can be pattern print. Just let them create it themselves.
This is a prime example. Sorry for the pun. But this is a prime example of where you build up sufficient infrastructure for something, digital printing in this case, paired with a mixture of in house models and your own Amazon Bedrock hosted, third party, and open source models, turn all of that on and all of a sudden you can offer a very, very different model of clothing. I don’t know how this will play out, because I said I don’t have an exact read on how people feel about it, but it will work. From a technology point of view, it will work, and that’s interesting.
Ben Hanson: That is the end of our first instalment of this. Grace, thank you for quizzing me. As always, I’m looking forward to doing this again next week, and you will see these shows now come out on a Tuesday.
So, every Tuesday, you’ll get this new edit in your inbox if you’re a subscriber to our mailing list, or you’ll see it pop up on Apple Podcasts or Spotify if you follow us there as well. The weekly deep dive interview shows are moving to Thursdays, so if you’re here for those as well, you will get those from me.
We have a big program of those lined up over the next 3-4 months we’re booking guests out to at the moment, and there’s some fascinating conversations that I’m looking forward to having there. So that side of things won’t change. If you want to see me interview people in a deep way, come here on Thursdays.
If you want more of this, if you want more broad industry news, my perspective, Grace’s perspective on what’s happening week on week in a more condensed format, we’re going to keep doing this as well, and we look forward to welcoming you back every week.