Tariffs, AI & the Future of Fashion: Chaos or Catalyst?

Good afternoon, everyone. It's just such a privilege to be addressing such a distinguished group here. I've had the opportunity to speak at PI PARALL multiple times, and it's one of the places I really enjoy interacting with folks because we're all industry folks and we kind of like understand each other's pain points. So it's great to be here. So we've— let me just do a quick introduction. Some people may know me, some people may not. I've been in the industry for 25-plus years. I've led product development teams for Ralph Lauren, for Eileen Fisher. I have done technology transformation projects for H&M, Nike, PepsiCo, some of the really large brands around the world. Most recently, I managed the creative technology portfolio for PVH, basically managing all of their DPC technologies and their B2B merchandising platforms. Currently, I'm implementing PLM for a billion-dollar brand, two blocks that way. I've also worked in academia. I've managed Pratt's Research Center where we were doing research in wearable tech, as well as I've taught a number of classes at Pratt in the graduate program. So that's a little bit about me. So what we are here to talk about today is basically the tariff chaos, or should I say the catalyst? I crossed off chaos because it's really, it's something tariffs are catalyzing the rate of change that our industry is experiencing. So we're With the proliferation of AI technologies and the geopolitical storm, this is a massive opportunity should we choose to accept it. And I don't think it's really a choice at this point. I mean, I think we're in it. So the chaos is undeniable and its impact on our cost, supply chain, and consumer confidence is absolutely profound. By a show of hands, how many of you have had to fundamentally think a core part of your operational or merchandising strategy in the last 6 months? Just a couple of people. There's got to be— everybody else is staying the course? Nobody's had to— I only saw 3 hands go up, which is— Pretty surprising to me. Are there a bunch of brands in the room or just tech providers? Can I see a show of hands of the brands in the room? Okay, so every brand pretty much raised their hand. Got it, perfect. That's what I expected. So as a longtime industry veteran that's immersed in fashion's technological transformation, particularly in pioneering digital product creation, scale-up, and AI applications as well as PLM implementation. I see this something else from this emerging turbulence. I see a powerful, undeniably harsh catalyst that is moving us towards an accelerating adoption of AI technologies. And we certainly heard a lot of this, a lot of it over the last day and a half here, and it's very, very encouraging. So the headlines from, you know, mid-2025 paint a very, very stark picture. We have persistently high tariffs. We have tariff whiplash where we have this oscillating, you know, tariff rate situation. We've got the de minimis landscape that is completely changing from 0% to 100% to 54%. It's completely disrupting e-commerce for us. Then add to this the US credit downgrade that just happened a couple of days ago. That US credit rating downgrade is really bringing a lot of anxiety in the financial markets. This will ultimately really pressure our margins, our cost of goods sold. And what this means for the average household is the average household will face an estimated loss of $2,800 per year. So, you know, that's quite a lot of money, especially when it comes to discretionary spending. The vulnerability of our traditional, often rigid, cost-focused supply chains have been absolutely laid bare. Does any of this resonate? Are you— can I, with a show of hands, like, does— is this resonating for the room? Yeah, yeah, that, that's, that's what I thought. So it's, it's increasingly clear that this isn't a temporary blip. This is the world that we live in, and all of this is probably just going to keep accelerating at some rate. And we're not really sure what's going to happen in the next 2 months, 3 months. So basically, it's creating like a storm. This is a perfect storm which is creating an undeniable burning platform, a non-negotiable non-negotiable mandate for deep systemic change. Many of us knew that was overdue, right? So we've relied on sort of like the fragility of our supply chains where we, where as an industry we have chased the lowest cost at the expense of kind of reliability. You know, we don't have the, because we have chased the lowest cost model, we don't necessarily have the ability to pivot quickly because we don't have alternatives. We've got very rigid sort of supply chains. So that's kind of what we are dealing with today. So then how do we, some, that's kind of enough about the problems. I'm not gonna dwell on the problems anymore. So let's talk about the actual solutions. So I'm going to propose to you three pillars And in good news, you've already kind of heard about these three pillars in some way, shape, or form over the last day and a half. So all of this should sound like very, very familiar to you. So with a quick show of hands, how many organizations in this room are actually actively using AI beyond just the standard reporting? How many of you are using AI to make critical forward-looking decisions in your merchandising planning? Okay, that's great. So it's a journey. It's kind of a journey for all of us, but the urgency has never been greater. Where I've seen and personally driven significant impact in moving from reactive to Excuse me. Where I've seen personally, where I have seen and personally driven significant impact in moving from reactive to prescriptive operations is in the field of demand sensing. In a market where consumer sentiment turns on a dime, we can shift the Sentiment can shift on a dime due to economic news or price changes. AI's ability to analyze vast real-time data set offers a massive leap in forecasting accuracy. We're not just talking about small improvements. My own team at a previous client, we've seen very tangible gains here which directly impact the risk of our inventory. And also the other thing is the supply network intelligence. Imagine using AI to constantly model the financial impact of the various tariff scenarios, which are constantly changing across your global footprint, or to simulate the ripple effects of a sudden port closure or supply disruption, and then prescriptively suggest the most resilient resilient alternative pathways in real time. This is about anticipating and mitigating and not just responding to it after the fact. So yesterday, I don't know if some of you saw the Impact Analytics presentation where this topic was actually touched upon. So there, there are a variety of solutions, and I, you know, I'm not advocating for any of the solution providers, but there are a variety of solutions providers out there that can actually help you in, in this arena. And I would say that it's almost really— you're— it's almost— I'll, and I'll go as far as using the word foolish if you're not actually taking advantage, advantage of these technologies, because these technologies are here, they're here now, and you really owe it to yourselves and to your companies to to actually sort out these technologies and try to figure out how to ingest them into your tech stack, because this geopolitical situation is, is very, very real. And of course, all of this feeds directly into your inventory planning and your pricing optimization. With margins under siege, AI can help us understand price select elasticity product by product, market by market, allowing for smarter pricing strategies and more precise inventory allocation to maximize sell-through and minimize markdowns. Anyone else using that, any of these modules for price? Nobody, okay. Huge, huge, huge opportunity. Finally, as we are all rapidly diversifying our sourcing, AI tools become invaluable for automating aspects of compliance and risk assessment. I recently was a— I was recently at an EY meeting, one of the large consulting firms, EY. And it was— I was surrounded by a group group of C-suite folks. And it was really incredible to see. They were not necessarily all old-fashioned folks, but there were, you know, some other companies as well, but all in the retail space. And it is really amazing, like, how much excitement there is about this specific piece, because we know that with the credit rating downgrade, there's going to be— the US consumers will feel it. They'll feel it in the cost of borrowing. They'll feel it in their credit card rates. So it's really, really important to understand price elasticity and how that will impact the consumer. So I guess I'm just gonna open it up to the floor. So for those of you who are already on your AI journey, what's the one area where you are seeing AI provide the most immediate tangible relief during this current climate? Can just shout it out. I thought some of you were already using AI. Any takers? I think the auto-replenishment. Auto-replenishment. Yep, auto-replenishment is a really good one. Anybody else? Okay, we will keep moving and we can have a private conversation afterwards. Okay, so pillar 2, digital product creation and PLM, which is our agility engine in compilation with AI. How many people in this room in this room have DPC technologies, digital product creation technologies in place? I personally know, yep, I was gonna say I didn't see your hand go up. So thank you for that. I know Ralph does. Anybody else? What company? Yes. Okay, awesome. So if you are not leveraging, leveraging DPC in your operations, that is another huge opportunity. We know that digital product creation can really, really help with the price of your salesman samples, and especially when you are in a situation where you have to quickly pivot from one country to the other rather than incurring the cost of sample product development and sample development. DPC can be very, very valuable here. I've personally implemented digital product creation at a bunch of different companies. I'll take the example of H&M, right? So a couple years ago I worked on a project scaling DPC for H&M. Now H&M, as we know, is a huge company and has millions and millions of samples. In fact, during this project I spoke to some of their vendors from Bangladesh and they explained to me how just out of Bangladesh they have an abundance of— and I, I can't tell you the exact number, but it's actually in the millions. So when you are producing, you know, millions of samples a year, like, imagine the cost differential when you can get away from that and actually, instead of doing actual physical samples, you can move to digital product creation and have virtual samples. Like the price difference there is astronomical and the other factor that is really useful is that you can do all of this virtually without ever having to get a physical sample and it's actually really, really fast as well. So we've, so I can, we can consistently consistently see how replacing the endless cycle of physical samples with high-fidelity 3D assets can cut weeks and even months from your development timelines and eliminate enormous portions of sampling and shipping budgets. For those of you— I guess I've already asked this question, but for those of you who've had the opportunity to scale DPC significantly, what is the most impactful, perhaps unexpected benefit that you are realizing in this specific economic climate? And if you have, if you are, you know, you can think about it, and if you haven't, that's something, you know, for you to think about. Beyond cost and speed, DPC also creates a single source of truth within PLM, which is absolutely vital for effective collaboration across globally dispersed design, development, and sourcing teams, especially as we onboard new partners rapidly. So if you have a PLM system, a cloud-enabled PLM system, which you are using in conjunction with DPC, it creates a single source of truth that you can leverage very, very quickly across geographies. And if you have to pivot very, very fast from one region to the other, then you've got the single source of truth that you are able to leverage. PVH does this particularly well. They've had the ability to scale DPC quite drastically basically. I don't know, Steve, you're, you're in the room, so you can, you can, you can speak to that as well. The, the other thing with DPC is because there's— it's not just about sampling, right? So once you've got DPC in place and you've got those digital assets, you can also use those digital assets for e-com purposes. You can run your digital showrooms with DPC assets. During COVID PVH really utilized this really well because all of the showrooms had actually shut down, so we were able to keep our appointments digitally. PVH has, you know, multiple installations of these digital showrooms across the globe, and it's really easy if your buyer not come to a physical showroom. You can do all of this digitally. They can do this from home. So that, that's the other advantage that DPC offers in conjunction with PLM. The other thing that also happens is when you've got DPC and PLM together and you've got the single source of truth, all of that data is extremely valuable in running your AI systems, right? Because AI needs data, and it needs good data. We've heard several times today, garbage in, garbage out. So if you've got, you know, good data that is being generated via DPC, then being leveraged into PLM, it kind of also provides the backbone of all of your AI data. So that's the other advantage that DPC and PLM offer. Together. Okay, so the third, the third and the last pillar. So we've talked about the critical role of AI, the power of DPC and PLM, and the necessity of building resilient, building these resilient value networks. So none of this happens without a significant evolution in how we lead. The profile of a successful fashion executive as this new era looks quite different. We're moving from a world where we could perhaps rely on historical data and gut instinct to a scenario, to becoming a scenario strategist. We have to constantly ask about, you know, what if, what if around different futures, and we have to start building optionality into our planning. We are dealing with a lot of ambiguity, and that's what we are trying to master. It's no longer enough to just approve tech budgets. As leaders, we need to be genuinely tech fluent and data-driven visionaries. We just had a panel around implementing technology and change management earlier this morning, and Somebody said on the panel that tech projects, the AI projects are not tech projects, they are business projects. So anytime you are implementing technology, just remember that IT shouldn't be driving any of these projects, right? The IT is there to help you, support you, but they're not there to lead. Lead the projects. These are absolutely business projects and, you know, that's how they, that's how they should be driven forward. And the role of integrated change management becomes super important here. So if you are, if you are a leader and you are running an AI project and your change management management strategy is sort of like an afterthought, that's not really going to work, right? So I just was talking to somebody about this a little bit earlier today, is, you know, you very often— what I have found in doing these types of projects is you start an AI project, you get halfway through, and suddenly people realize, oh, we should— we— there is a need for change management. And at that point, it's usually too I mean, I've seen a ton of projects go south because you didn't think about an integrated OCM strategy upfront and really figuring out how you're gonna enable people, how you're gonna support people through all of these different changes. So that's something that's super important to think about. The other thing I also wanna talk about is that this sort of environment also demands that we become global network orchestrators. We should be adept at building and nurturing complex, often cross-cultural partnerships. It's kind of less about command and control, and it's more about how do you influence and collaborate with people across geographies. And the other thing is that when it comes to sustainability, our role as leaders is to champion an integrated and verifiable moving from peripheral CSR function to a core driver of business value and risk mitigation. When it comes to sustainability, accountability. It's about demanding proof, not a promise ethos. We are also seeing now, despite sort of the political climate, we are still seeing the SEC go after a lot of companies that are indulging in greenwashing. There, there's been several fines over the last 6 months where companies have announced, you know, made some very vague statements and the SEC has gone after them through their 10-K filings because there are some very, very vague statements around sustainability. So these are all of the sort of like different strategies in pillar 3. So now I'll move to, What does the new leader, the new fashion leader look like in this era of global economic uncertainty? So we've seen the powerful tech solutions, but who makes all of this happen, right? Who is the person executing all of this? It's us. It's everybody in this room, really. Our roles are changing very, very, very fast, and it's actually a pretty— despite all of these challenges, it's a really exciting time for us to lead. We are moving from forecasting a stable past to becoming scenario strategists. We're embracing ambiguity and designing for the unexpected. Technology isn't IT's job anymore. Like I said, it's really our job and IT is there to support us. How many of you in this room feel that you've got C-suite leaders who actively are championing and fluent in the strategic application of AI and DPC? One person, two, two, three. Okay, amazing. Half. Yeah. So, you know, what does all of this boil down for us in this room? Leading our teams through this relentless pace of change comes down to two things. It comes down to making smart, quick decisions based on solid data that AI can enable. And at the same time, It's about genuinely supporting our people. It's about supporting the talent that actually makes all of this transformation happen. It's leading with empathy. It's understanding that our people are going through the same sort of transition in this economic uncertain times that we're all going through and leading with empathy. So I'd love for you to think about for a second, what's the one key thing that you are doing right now as a leader to help your teams tackle this tech-driven and often unpredictable world that we all now live in? Just take 30 seconds to think about it. We're getting to the end here. I understand I'm the only thing standing between you and lunch, so just bear with me for a few more minutes. So as we confront this era of profound disruption, I want to discuss distill our discussion into 3 core imperatives. One, embed AI and digitalization as your core operating system. Two, architect antifragile collaborative value networks that move you decisively beyond optimized, outdated linear supply chains. And three, lead the human and cultural transformation by aggressively upskilling upskilling your talent and fostering an agile adaptive culture. So as far as the, the, the first principle is concerned, when you're looking at technologies such as DPC and AI for predictive intelligence and adaptive execution, these are all the backbone of innovation. These are no longer just some peripheral technology. Technologies. They have to become the very fundamental way in which your organization senses, decides, designs, and delivers value. They can provide the measurable gains in speed, cost, and accuracy. And all of this is completely undeniable. And, you know, I've been part of transformation projects where I see this firsthand, and I'm sure there's a lot of people in this room who have done these types of projects and are seeing value from these projects as well. I would highly recommend you, you know, going out there if you haven't, talking to some of these technology providers. I don't make a commission, I'm just, um, an honest recommendation to— if you haven't started that journey, then, you know, I, I would highly urge it. Second, shifting your entire strategic focus on architecting antifragile collaborative value networks, moving decisively beyond optimized, outdated linear supply chains. This means intelligent risk-assessed diversification, fostering deep transparent partnerships built on shared goals, and weaving sustainability into the very fabric of this network as a source of strength and trust. So gone are the days of when you had your linear relationships with suppliers just based on cost. That's not going to work anymore because there's only so much you can squeeze. So based on this, you really have to start leveraging and collaborating and having true partnerships with with your suppliers so they can help you pivot as, you know, geopolitical winds are shifting. And the third, which is around human and cultural transformation, you have to aggressively upskill your teams. You have to invest in your teams because your people are your most critical asset. Championing enterprise-wide data literacy, fluency in AI tools, and a mindset geared towards continuous learning and rapid adaptation is not just important, it is existential. These are not just abstract concepts. These are proven practical pathways to survive the current storm and to emerge as leaders as a resilient fashion industry. And I'm very, very optimistic that we can absolutely achieve this. We've done it before. We've done it multiple times before. And this is just another curveball that we've been all thrown. So basically, this is sort of like the end of my presentation. And I'd love to hear your thoughts I'll take a few questions. I hope I've given you some food for thought and some things to think about as you are leaving today and going back to your day jobs.