10 Best AI Use Cases for Ecommerce in 2026: Ranked by CEOs

Welcome to the operators podcast. This is the AI Throwdown Edition. We are going to rank the ways that you should be using AI in your business. We're going to yell at each other, argue, disagree. And at the end, there's going to be a harmonious package that you can take and turn into profit in your business. At least that's the hope. Today, I'm joined by the core four, the originals. We got Sean, we got Matt, we got Jason. These guys are absolutely using AI every day. They're at the frontier. And they're going to share with you how they would rank the best use cases. How are we doing, everybody? Awesome. And guys, I heard that Ernst and Young is going to be delivering the final tally of the floor of us at the end of this thing. These results, the tabulated results of what we came up with are guarded under a walking key. We've had independent auditors go over them. So it's the best kept secret in Ecom. And we're going to reveal it on this show. I sound really old when I say Ernst and Young guys. It's EY, sorry. All right, slip it over. EY, yeah, don't date yourself. Dude, yeah, I'm excited to be here. This is going to go awesome. And that's what I'm going to say. If you're still using blank AI tool, it's done. That's the worst one. Sean's actually launching his own AI tool in this. Sean AI. So we'll talk about that during the sponsorship reads. Matt, what's going on with you, man? I am AI Redpilled at the moment. I can't, I can't. I don't think I could actually spend more time building stuff right now. So this is the perfect time for the two of this episode. You're like fully jacked into the Matrix. You just you plug a USB end to your neck. Yeah, if there was an IV drip, I would probably have it. We are going to talk about the best ways you can use AI in your business. Perhaps there's been no bigger word in 2026 than AI. In many ways, this was probably the year that AI became truly useful in building your business and an enterprise. It's more of a toy chatbot before. And I think with the kind of explosion with Cloud Code and then Codex, like, now you really can build amazing things. We're really starting to see transformation in our businesses. But it's almost overwhelming. You know, you kind of said it, Matt. I think we've all felt the-- gosh, there's like so many tools. There's so many different ways to use this. But we need to focus where do I use it? Where do I start? And that's what we're going to try and give you in this episode is really practical. From our point of view, how you use it and what areas of your business are the best to use it in. So here are the choices we came up with of areas of your business you could use it in. And what we're going to do is we're going to go around the world. Each of us is going to tell you how we rank those choices, what the best one was, what the worst one was, underrated, overrated, and then we're going to give you, like, hey, if we kind of tabulate and average all that together, our group consensus about where you should be spending your focus when it comes to AI. So the choices that we looked at were content creation, customer service, data and reporting, internal knowledge base, leadership and people, market research, operations, paid media, product development, website, and CRO. All right, are we ready, guys? Let's do it. Here we go. Jason, we are going to start with you. When you hear those lists of different ways you can use AI in your business, obviously, you're in the weeds every day with hex-clad, huge business. What is the most underrated and what is the most overrated thing on that list? But before we go into it, I was really trying to figure out how I got chosen to go first on this one, honestly, and it's probably because you guys know I'm going to be the fastest, and I'm not going to suck up all the air time that you guys will. So I'm thinking that's it. You've already used 30 of your 60 seconds, Jason. So you better speed this up. I mean, data reporting has been a game-changer for us at hex-clad, like I was thirsty for information. And this is how we got it, combining our data warehouse with Saras, fulfill, MCP connectors, building stuff in Cloud Code, all that stuff together. My ops team has amazing dashboards. I get daily reporting on our company performance that I literally would have to pick a hunt and pack through spreadsheets for, with note I get it, with a narrative. For me, this is all personal to me, right? Because I'm not in the weeds necessarily on a lot of things. We have great teams at hex-clad. But it's made me a much better manager, and it allows me to really focus on making strategic decisions. On the content side, in terms of worst for us, like, hex-clad pans do not render very nicely. And so I think content is probably great for apparel and other things, where you need multiple callers, offshore simple modern and Pila and even Ridge are probably getting a lot out of that. But we get very little out of that. So that's top and bottom for me. Sean, what do you think? Is that a hex-clad specific thing on content? Or do you think that's a more generalizable thing that it's still hard to make good content? - I think it's internal to hex-clad because they have a team that doesn't want to embrace it. I'm telling you, shots fired, Jason. - I love it, I love my Sean blows up what we do. It's great for us. - Yeah, I'm telling you, go into my ad account right now. Look at all of our statics. They have AI as a huge piece of them, right? And I have a beautiful ad account right now. I can send over some great creative. I get not trusting it for video yet, because it's hard to get relevant good videos, where it takes a lot of skill. But you take the render of your pan, you say put it in this kitchen with this chef, you're getting great statics coming out of it. And if you guys want to, I'll do it right now live on the podcast. I could hook, I could jump into Higgsfield and I can generate these in less than 30 seconds. They have great statics you do want to run. - You should do it while we're talking, Sean, and then show Jason what's possible. - I must say, with my content team, I'm sure they are using it for statics and stuff. I guess I haven't seen it as a super massive unlock, but I just may not be educated enough on the subject. So hey, maybe I'm wrong about that being the worst. - I think when you're running something like Higgs Cloud, you were already producing great content, but the quantity of content that you can produce that's really good is dramatically increased by AI and the cost per piece of content can be driven way down. But it's not like what you guys were putting out there is gonna be made better by AI because it was already excellent. But as a big part of the game in '26 is like what is your volume of creative content? How many different shots on goal? How many different looks can you get? And I think that's what I'm hearing you say, Sean, is like the ability to scale up to hundreds, thousands, tens of thousands of creatives with AI. Obviously that is just not doable with human effort. - World-class graphic designers are hard to find and expensive. AI brings everybody to maybe not world-class, but top 5% designers. If you have good ideas, you can produce them. And for statics, it's an entirely salt issue. Like if you have a brand and you're doing email or landing pages or static ads, like AI can definitely do that once you have good resources, like just good base assets. Videos are still hard. And I'll give everyone a lot of credit that like it's very hard to get a good brand video because of like the product fidelity, right? Like holding the product to be consistent and seeing the scene to scene, they're working on it though. - We didn't say this specifically, but an example that we're seeing in another context is we've been working with Cody on something and he started this project and within 24 hours he had this unbelievable email system built where you give it personas and you give it the different email kind of emails you want in your flow and you give it different hooks and you give it different offers and you give it different images and you show it other people's imagery and offers and then it's able to, it's ability to generate emails is pretty remarkable. And I think that this is gonna be kind of a theme of this episode is the ability to turn things into systems that were a lot of individual tasks in the past. Email might be an example of this and what I'm seeing the very best people do is they're able to systematize their use of AI. So it's not just like, hey, I can create a few static images with AI, it's that I can rethink my entire email flow where I can build this thing that's automated and it's constantly testing new creative and it's constantly learning and getting better that's built off of all these subsystems. What Jason is hitting on is still a little true, like very intricate product details, like design details, it still does screw those up sometimes. Like we have this problem at PLA still, right? Like some of our designs in our cases just are so detailed that when you ask it to render that case, that design into something else, it'll mess up some part of it. So our rule for this, and Mike, I think you're hitting on it, is like we looked at it like what's the workflow for this? So we generate a lot of them, but then we have other AI tools that will evaluate the quality, the image. The one place that we've had a hard time using them is actually on PDP. So like when somebody is making the purchase, their, our view is like, their expectation is that the image of what I am seeing is what I'm gonna get in the mail. And if AI screwed that image up in any way, that could create problems for us, right? So we tend to still lead with like an actual render of the. product because we can't have it hallucinate some part of the design or some part of the color. So I think depending on how detailed the fine details of the images, they do still produce weird results. But I think that you solve that Jason which is workflow. We'll just make a hundred of an image and then have it pick the three best ones based on like fidelity and then a human can check it and that's been the unlock for us. We save thousands and thousands of hours in photography every year because of this. Look, and I'll say that we're rendering more things than ever before. We're doing more product photography than ever before, but because it's such a good base to then go build assets off of, right? Like, you know, we have a studio that shoots every single day. We take that and now we can we think that one photo that we took that we love and take it to 50 different directions and to tie it back to what Mike was saying. I think the future of email agencies is entirely cooked like, you know, Mike said, take, you can take hooks you like, you can take emails, you like, you can feed it into cloth and you can, you know, get great emails coming out of it. What I, what I did over the weekend was it's hooked up to my dam. So like where a digital asset manager, it took up to my go-to-market board and I just said, make me all the emails for these campaigns. And I did not feed it hooks. I did not feed it promos. I did not feed it everything because it's stored in my internal company database. And I immediately got 50 plus emails that are good enough to run. So it's, it's not even like, you know, you have to labor over what you're feeding it anymore. You can just say, make me good emails and it just shoots out emails. So the future of email is, is totally disrupted. And this is probably going to be an indication of how this conversation is going to go is that even some of these areas that we're not getting a lot of use out of right now, they're, there are ways to use them. Like so Jason, this might be last on your list and it doesn't mean it's not usable. It's just like, hey, you guys haven't found a way to unlock it yet. But Sean, you said something really, I think important, which is there's a direct correlation between how much context you can feed AI and how useful it can be in your business. Fulfill is the ERP built specifically for D to see any commerce brands. Inventory, purchasing, warehousing, financials all in one system built for the way your operation actually runs. There is not an ERP on this planet, not one that has more direct 3PL integrations than Fulfill. They integrate with over 400 3PL locations globally. And most you listen to this right now, either running your own 3PL relationship or you're about to. And the second you're 3PL and your ERP aren't talking to each other on real time, you're flying blind. You don't know your true landed costs, you don't know your real margin, you're reconciling spreadsheet to 11 PM trying to figure out what $40,000 what I know because I am on Fulfill. The visibility we have now versus what we had before, it's not a marginal improvement, it's a different game. Fulfill is the only ERP I've seen that was actually built from the ground up for D to see and it's not some bivocated piece of crap. Believe me, those exist, Fulfill isn't one of them. Go check out Fulfill, tell him Sean's saying. Jason now give us your ranked order of all of those things. So we did data and reporting, customer service, huge, right, just money, that's just money there. I think that kind of, it does come together with a few others like, well, there's market researchers, product development, internal knowledge base, operations, paid media, websites zero, and then content creation, like there's some overlap in why I feel the way I feel about a lot of these, but I just think on leadership in people, it is, the AI is like having an advisor around all the time. And I just find that it gives me great ideas in getting stuff done and a big part of this is, and I'm seeing this across my organization, not just Jason, right, but like, I'm seeing people do really good work and take leadership positions and roles on projects and the ones that are doing it right, I mean, it's pretty amazing like there's people who I like, I really thought were not like very productive and they're embracing it. And they're actually saying, wow, I can actually do stuff now. It's like, it's on, I think it's unlocked people in a lot of ways, the people who are really like, say, I think the people who are embracing it, you know, it's been a big unlock for them, you know, and that, that's just kind of where I look at it. This is a great segue map because this is your least valuable was leadership in people. So it's a great transition to you that it's third on Jason's list and you ranked it as the least valuable. I think I might have ranked it as the least valuable, even listening to Jason is making me rethink my choice. Why did you rank it as last? Yeah, Jason's making me rethink mine now, thanks, dude. I ranked it as last and I put this comment in like, please for the love of all things holy, please, like, don't allow AI to manage relationships in your business. So like as a leader, I just don't think you should outsource leadership to anybody else, not even like let alone an AI, I guess is how I looked at that. But Jason, I think I didn't come at it from your perspective and it's actually making me think Mike, like, do we all have a, has the bar for mediocre gotten higher? So like, you know, AI is making like your best people like a ten or a hundred X better, but is it making people just good enough to keep them now? I don't think so. My observation is that somebody's ability to contribute to organization is a combination of what are the developed skills that they have and what is their drive aptitude intelligence. And that there was a time where it doesn't really matter how much drive aptitude intelligence you have. If you don't have certain skills, if you haven't gone through certain apprenticeship, you're just not able to contribute. And one way that I've seen what you're talking about, Jason, we have interns this summer that have produced things that we are leaning on pretty heavily in production on the website. And that is, I mean, they started in late May. And that would have just been unthinkable a year ago. And like the analogy I would draw here is that in like engineering, software engineering for a long time, there was this idea of the ten X engineer or the hundred X engineer, but there really wasn't the business equivalent of that idea. You know, nobody's like the hundred X accountant, but I think when you add the ability to be like basically a hundred X engineer on top of any person, then now you're starting to see that idea on the business side of like, wow, yeah, you really can have the hundred X analyst, the hundred X, you know, CFO, whatever else, because now they're able to systematize their skills and it really is more about driving ambition than it is about how many skill individual skill sets do you have? I think you're right about it, but you know, I think there's just certain people who they found the ability to unlock themselves better to add more value. I just think that's a cool idea, Jason. What's a specific example you've seen that, Jason? Like, I don't want to call out specific individuals at the company who have like impressed me, like with, you know, they would, they've been able to do work and bring thoughtful positions on things and they would never have gotten that without cloud, right? But it's like, the fact is that they went into cloud and did the work, right? And then they came back with like thoughtful position and thoughtful information and they, there are people that just, I feel like they just didn't know how to get from point A to point B and like, this has been a huge unlock for them. I do think it's taking like the average person and making them better. And that's what, if they, if they embrace it and that's, and that's what's supposed to happen with AI. Yeah, it's a development tool. Look, Jason, it was, it was near the bottom of my list too. So I think you are changing all of our mind. The beauty of the technology is it can teach you when you get stuck, right? And I'm sure there's like all of us have tried to do something very technical in our lives. And like, I would always get like 80% of the way there that I'd hit a roadblock and like, I don't know how to go forward, I don't even know how to Google the problem having right now. And at least, Claude is there with you and can just tell you what to do immediately. So I do think it lets everyone become technical, right? Like, you know, Mike and his interns. And I just didn't really understand what leadership and people meant in this exercise. I'm like, what the hell does, am I using AI for leadership for? But I think the people piece, if we can unpack that and treat that separate, we're recruiting for some roles right now. And if you have a remote job in 2026, hold on to that thing because I had a remote job opening and I got like 2000 applicants, okay, it's been live for about four days. So like, the job market for remote jobs is crazy. How do you go through 2000 applicants? We have tons of people, you know, when you apply, you have to like answer a questionnaire, right? Then we have AI go through and rank that questionnaire. So we have Claude to it first, then we have Cheshire PT do it as well. And so we have double AI rankings. And then it took up to my Claude so that I can ask questions, be like, hey, bring me the top 10 people who have e-commerce experience and don't live in California, right? And now I have BAM out of 2000 people, triple ranked with AI people that I should actually talk to and it way saves time. So the people side, I moved that up, leadership, I still don't understand, but awesome one. If you're a founder using AI for analytics, you know the trap Claude, plus BigQuery, gets your answers that are fast and wrong or slow and right, never both. The problem isn't your analyst, your data, your tools, it's your business context gap. Sarah's IQ fixes that. Conor, who runs my marketing, cut his reporting time from 10 days to 45 minutes. IQ answers in plain English, built on your business logic, consistent, deterministic, and fully transparent, with the assumptions and sequel behind every answer. Same answer whether you ask, your CFL ask, or your board asks. And if you're a Claude user, the IQ MCP is ready to plug in today. Claude plus BigQuery isn't enough. It needs your context. Get it at the link in show notes, or go to seroscentiletics.com to learn more. Well, one of the ways this is the most obvious in my mind is that AI is definitely going to impact the size of organizations. And so it might be number one in that sense that just size of team is going to be transformed by AI. It's probably my single highest conviction. Teams are going to be smaller. The data really bears this out. You're seeing more small new business formation than ever before. And just in general, it makes sense. Leadership is hard, and managing people is hard. And the more people you have, the harder it is to manage. If you can, everything else being equal, get the same output from 20 people that you could from 40 people. That 20 person organization is going to do better because it's going to be tighter, more coherent. Less things are going to be dropped. There's going to be less overlap and responsibility. There's going to be less politics, less issues you have to deal with. And I think all of this is going to be pushing organizations to be much more compact. Not surprisingly, we're seeing this in a lot of the e-com companies that are ripping right now. These are people that are technology AI first. They start with small teams. And then as they scale, they're not particularly compelled to add a bunch of people. And I remember when, you know, like I would go to, I don't know, business leader gatherings. And like they would all ask, like, well, how many people do you, you know, employ? How many people work for you? And that was like a badge of honor. I feel like it's almost inverted. Where now it's like, how few people do you employ in order to run your business? And so we're certainly seeing that play out already. Yeah. We'll add very close to a hundred million dollars in revenue this year. I actually have to pull the exact number. How much I think we're going to add in revenue over last year. And it used to be, if you had a hundred million dollars in revenue, you'd add a hundred people, right? Then it'd be you had 50 people. I might add five to 10, right? So we're talking about, you know, 10 million dollars per new head added in revenue. And it's because of leverage in AI systems. So we're still hiring. Teams size is going to grow here, but disproportionate to revenue going forward. And here's the beauty of that, Sean. When you do less hiring, like the more revenue per person at your company, the more opportunity you're affording that person, the more opportunity to earn more, the more opportunity for scope and advancement. And so like, I think there's this negative stigma about AI of like, oh, it's going to take all the jobs because of what we're saying. I don't think that's the case at all. I think it's going to redistribute jobs. And I think because everybody at your company has more responsibility, they're going to be able to earn more. They're going to be able to grow more. And that's a good thing, not a bad thing. Yeah. Look, this is an aside different episode. We should talk about how expensive things have gotten because I remember in 2020, if you offered somebody a $60,000 out of your job, that was good. You know what I mean? And now, like, it looks like the minimum you have to pay somebody who knows how to use a computer as a hundred grand. And it's like, maybe this is just me being a boomer now, me getting out of touch. But like, I remember making a hundred grand for the first time being like, this is crazy. I'm so rich. And like, I think real inflation's probably been 10% a year for the past six years. Because now I've a 10% for six years, compounds real fast. Yeah. I got people asking for, you know, 180 for jobs that I used to pay 80 grand for. It's crazy. Matt, you know, our friend Shireen had a great tweet on this subject. He said, the biggest threat indicator that AI can take your job. Someone needs to tell you what to do. If someone needs to tell you what to do, how to do it, and when to do it, you should be very concerned about your future and find a way to fix it. So that was Matt, that was your last one. I think we've all kind of like maybe reconsidered our stance. Jason, you moved us around. That's good. Matt, what was your top one? My top one is actually, so I don't know about you guys. I had a really hard time ranking. The top five. Because they're all so close and their value to me and they were like in a company. But I went with my number one was internal knowledge base because I think the more context and more memory that these things have, the more powerful they get. And I actually think that competitive advantage right now, I mean, we talked about this years ago with Ridge that because Sean had sort of enforced this like write everything down mentality because they're a remote company that that has actually made them much, it actually enables them to go much faster and adopting it because like they have an incredible amount of like internal intellectual capital that is documented in a way that is AI friendly, right? Whereas like most things are in people's heads. It's not very useful to AI. So for me, I chose this one because I think it sets up the rest for more success. Personally, like having a Hermes agent with a G brain and a chief of staff that like literally has, it's like a twin of my brain. Everything I do digitally is stored in this G brain thing. Is incredible leverage, right? And then now doing that at a company level like standing up a new company from day one and focusing first on like getting context into the place that AI can use is making the content creation piece better, market research better. Like even how do we want to set up data architecture in this company? Like we need to know how the company is going to run. Who are we serving? Like all that stuff seems to be getting better with more context. And then I think shared memory and shared skills and all these things like AI is a single player mode. No question people are getting a lot of value out of that, but I still think AI multiplayer is a big unlock for companies. So that was my number one. That's why. Jason, what do you think about that? Dude, I just went for a 20 minutes. How about we ask Sean? Jason says 20 words. He's like, I'm done. Guys, I'm done. I'll see y'all next week. I'm just trying to let everybody get their chance here. Yeah, unfortunately, I think I have talked the most, but I'm happy to share that that we've we got so lucky that we embraced being fully remote. And I do not think in person teams have any advantage in the in the age of AI, simply because by being remote, everything is recorded, everything is written down, everything is documented. And we got like, this is like, it's better to be lucky than good. We fell so backwards into that, but now I have everything for the past six years recorder that I can feed into an AI model. And that's why I said I hooked it up to notion. I just said, make me emails. I don't need to go hunt those down. I don't need to go pull them from my favorite website or whatever, because I have six years of them documented in a folder somewhere and every conversation, every slack, it's just, it is a huge advantage to have the everything be documented right now. And I fully agree that it's it's it's a kick and ass. Most AI tools in software don't give you direct ROI every month, but post script does. I run two post script AI products at Ridge both show up on our PNL. Infinity testing runs continuous AB tests on our SMS automations completely in the background. It's driven $446,000 in incremental revenue, not just attributed incremental. That's a 32X incremental row as with click the rates up 43%. Then there's shopper and AI sales agent that answers every inbound text in under 40 seconds. We're running 23X ROI on messaging cost of loan. If you want SMS software that gives a proven ROI, go to post script.io and book a free demo. When we first started embracing AI, like the first thing I wanted to do and it was sort of, it was this internal knowledge base. And like you just you just have it shone because you you documented all that stuff like really, you know, really early on. I actually don't even know what the status of that project is. I got to go check on it. I just asked some people to do it. But like seriously, there's, um, but you know, we're not going to get into remote versus in person here. I'm going to I'm going to not do that. We don't need to litigate that. No. But I do I do agree that it's a benefit that we were not thinking about two years ago. And like when we we've had a lot of discussion about this and I would say for sure it's something that has changed the calculus, even you know, somebody who's like kind of been like, Sean, you're just wrong on this, you know, like, it really has changed the calculus. You know, one of the things that makes me think about, uh, there was a point in Amazon's history where Bezos sent out a memo and basically the memo was like, everything is going to be externalizable. Really, what he was saying is everything's going to be API based. It's just going to be. And if you don't like that, that's fine. You're fired. And he just, he just said, that's the way it's going to be with everything inside of Amazon. It has to be API based. And that single decision led to AWS and probably the core of the modern internet in the cloud. And I think in a same in a similar way in your company, you have to put your foot down that we are going to document our context. You have to because what is really depressing is when you look at your organization and you kind of say, what am I paying? I'm buying all these hours from people. What am I actually getting? And you realize like 40 or 50% of those hours are just people trading around pieces of information. And for the first time, you can really be like, like, for example, Jason, you're like, I don't know where that project is. We're herodeling towards a future where it's like, you just ask, Claude, where, or, you know, chat GPT or whatever codex. Hey, where, where are we on this project? Yeah. And if you are in person to one thing I would That would do, 'cause I had an impersonating yesterday. You have to record it. Guys, these things, like, that was the same thing as Sean, what an unlock to just do that. Just carry one around. Yeah, and I would make a mandatory across every office, every meeting, granola notes, because like, we had a big meeting maybe a week ago. We're talking about, like, some very nuanced product decisions, like, what type of product this is or whatever. And we recorded the whole thing, and then I just said, hey, Claude turned this into a one-page visual chart. And it did. And then I can, now I have to have a little poster. I can send everybody, hey, here's how we made these decisions. It's a visual graphic you can easily understand. Yeah, I mean, look, that is why I have one of these. This is a plot. It's a digital recorder. It does like automatic AI summaries. It gives my transcripts. My chief of staff can just grab everything from this every single day and store it in my digital brain. I highly recommend that if you are in person, you get one of these. All right, Matt. So we've talked about an internal knowledge base. Give us your entire ranked list. Yeah. And again, I think all of us are a little colored by like our experiences in our own companies. So my list is internal knowledge base number one, content creation number two, market research number three. I'm a copy guy. I spent a lot of time thinking about personas and angles. So like, this has been widely valuable just to be able to research what customers are saying. Data reporting was number four. Operations was number five. God, I had a hard time with this mic. Like operation is so valuable in supply chain. Customer service six website and CRO seven paid me to eight. Nine was product development. Ten leadership and people. Yeah, I had a really hard time. I could rearrange like six of these and argue all of them. Yeah, maybe that's an indication of where we're at that it wasn't, I mean, I think a year ago, if I would have looked at this list, I would be like, I feel really confident in one or two of these use cases. And even in this conversation, the ones I ranked near the end, I'm kind of being, I'm having my perspective changed on it. It's just much more broadly helpful. So Sean, let's go to you. I want to hear your list. What was your number one way to use AI in your business today? Yeah, it's the same one as Jason data and reporting. Both of us are on the Saras Analytics stack. And I've talked about that and and what that means. Saras is the data warehouse we use. All that means is they take all your data from all your sources and then clean them up. What data? Product type, like product SKU, you know, it's very common to be selling one SKU on Amazon and one SKU on.com and one SKU on wholesale. And then they're all functioning the same thing with different names and different SKUs. So Saras comes in and cleans all that up. And then once they clean all that up, they build you a tablet dashboard, but I don't care about that at all. They have an MCP that hooks up to cloud. So you have all of your company data that's incredibly clean and then you hook it up to cloud. When I say company data, you have all of your sales, all of your marketing spend by channel, you have all of your expenses every single day coming in there. And so you get perfectly accurate, perfectly valuable data bytes every single day that you can sort and cut however you want with words in cloud. And it has cut reporting timelines of Ridge down to literally minutes, right? I used to spend, I used to, by hand, do every presentation at the end of every month and like, okay, here's what we did, here's what we closed out. And it would take me one to two days, right? Every quarter I would do the quarter summary. And it would take me three to four days. And now it's 17 minutes. I just go and say, hey, rerun this for this new month with this data, right? So when I say it's like the number on use case, it is saved me personally the most time. Everyone of my company can now pull whatever data they want. I think data is a big bottleneck when you try to make a decision around product upsells, product pricing, MSRP, sell through literally seconds, literally one ask of cloud because it's hooked up via MCP. It's totally changed the entire department. That is my best use case. I am the most passionate probably about this. I didn't rank this number one. I ranked number two. But one of the observations I would make is that all of us tend to use AI in our wheelhouse first. And my wheelhouse is like analytics. And what I would say is that I am using it now to produce outputs that are better than what I could do regardless of how much time I had. And that was pretty shocking to me. I thought that I would probably be able to automate and produce similarly similar quality outputs to what I could do individually. I could just do it a lot quicker. Let me give a really simple example of this. So with Trevi, one of the biggest things we're trying to do is we're trying to predict how many returning users you're going to have every day because these consumable businesses are all about recurring users and understanding your LTVs and what you can pay. So it's pretty big part of the business. And before I'm trying to do it on cohorts and I have these retention curves and it's taken up all the space in Excel. And it's frankly not very good. And over time, what I've done. First, my model has moved from Excel where I update things to its Google Sheets and it updates every single hour and everything's automated. It's constantly pulling in the most recent data. And what I did is I stood up all of these individual parts of the model. And so returning usage behavior on Amazon would be one of those parts of the model. And I'd stand it up and be like, hey, you know, we want to build a model for this, build me a model for this. I was working with Codex and so we build a model. And then I'm like, okay, great. Now I need a 60% improvement. And you should consider these three or four factors you might not have considered. And what they'll do, the models will do is they'll build a kind of like a theory of like, hey, here's how this could work. And then they back test it. And they have very mathematical ways of back testing it and saying, if this were the model and I back tested and I went through all the data, how much better of a prediction system is there? And then I just beat the thing. I'm just like, okay, great. Now make it 50% better. Okay, great. Have you considered this? Make it another 30% better. Okay, it's not good enough. Do it again. Do it again. Do it again. And I've basically built this thing to where at this point, what it does is it looks at every single user. It looks at what they've bought. How many sticks they bought? How much the total card size was? Didn't they buy on deal? Did they buy on a weekend versus a weekday? What flavor did they buy? All of this stuff. And it projects out every single user and what they're going to do in the future. And then it rolls it up into one forecast. And it doesn't 30 seconds. And mathematically, it just blows out of the water what I had. And it's just like a small like micro example of how like our ability to understand our numbers for all of our businesses is just going to go to an unprecedented level because the amount of compute, the amount of intelligence that you can throw at any individual problem is just so much greater than before. If you had told me that there would be a tool that would get me where I didn't use Excel, I would have said, I don't believe they'll happen in my lifetime. And my Excel usage has dropped off a cliff because I'm doing so much more of it through the AI now. If you're scaling any commerce brand today ads alone aren't enough. Afterself focuses on the one moment that every brand already owns after checkout and turns the post purchase moment into more profit monetize every order with post purchase offers and thank you page experiences without disrupting checkout or hurting conversion enterprise grade tech used by Gap Ticketmaster Macy's in target now driving results for brands like True Classic, Hexclad, Ridge and Jones Road. I would know. This is the reason I ended up buying three pans from Hexclad instead of two. Afterself is already generated over one billion in additional revenue for ecommerce brands. Revenue that doesn't require more traffic or higher cat. So check out Afterself and tell them that the operator sent you. John and I have very similar use cases here because we both were early adopters of data warehouse because we were smart enough to see the future. I think I think Sean has had like major. I have a major unlock with like I get a daily report. I get it because I just get it. I get a daily email. I get a weekly email. I get a multi email like all the performance of Hexclad just pulling straight out of, you know, out of the AI out of Sarah's and with MCP with Clod. We also, you know, my finance and accounting department is now really starting to leverage it as well to get better reporting. So that, I mean, that's just huge for us. Connor, my CMO said the Sarah's MCP will go down as the biggest thing we've done this year just because it has saved, you know, the executive team across the board, you easily 40 hours a month of work. And then everyone down stream saving 100 plus hours because a lot of their job is reporting, pulling in graphs, checking data, seeing, seeing sales, making those tweaks. And just to having it instant, like I really can't express the magic. And it's so hard because I want to show people, but it has my sales data. So like, it's really hard to like go out there and like do a Twitter post and like look how cool this is. But anyway, here's my real sales data which I'm not going to do. So anyway, it's pretty awesome. You have to have a data warehouse. And there are so many downstream benefits of that. I think that's one of the reasons why this is obviously at the top of the list. And the gap between me having an answer to a question, even a very complicated question is now seconds or minutes and not days. So Sean, what was the worst thing on your list, the least helpful in your experience? It's chose product development. It kind of sounds like like you guys are treating market research also as product development. Like, I was trying to get more from marketing. When I look at my list, I'll go top to bottom. Data reporting I think is a must have. I think customer service is a solved issue. Half the tickets this year are originally answered by AI or more. Content creation, we've battled that out. I think it's statics are entirely solved. Internal knowledge base, I think it's incredibly important. And with HQ, which is not to get into specific tools, but notion is a great way to build AI context. But like, how do you share that across users? I think HQ could do that. And then I have market research. And it's amazing for finding out, you know, what to sell, who to sell it to, who your customers are. But then at the bottom of my list, I have product development as my number 10. It's because AI is not good at CAD files yet. It is not good at, you know, like actually making tweaks inside of product files like, it could probably do it. But those are very fine details you need to actually do, right? It can help you maybe think about a category to sell into. But it's not going to help you think the, you know, the way Ridge needs to approach that angle. Every time it tries to do it, it's very ham-fisted. So it's my least favorite one. My experience with that, Sean, is that coming up with a concept is much quicker now with AI. But the problem probably here is that there's so much context that AI doesn't have about the actual physical world and making things for us. So like, for example, there's all these, like, rules about tooling. And all of our lids come through tooling. And so we'll come up with ideas all the time that we'll send it to China and they'll just laugh. They'll be like, yeah, that's cute that you would think that would work. And like, I think this is a good example of AI. AI can dream up stuff that doesn't really make sense in the physical world because it just doesn't have the context of the constraints that you have around the tools. It might make sense in a CAD file even or conceptually, but it just doesn't practically work for whatever reason. And you can design the coolest lid ever in AI. But if it leaks, who cares? If it's not durable, who cares? Totally. And we all have that experience working with-- there's product designers. And then there's design for manufacturing. And it's different things. The product design will be like, it's one perfectly molded piece, and it's all made out of aluminum and it shines, right? And then the person who actually does design for manufacturing, they're like, yes, it's going to be $80,000. But it's $8,000 if we make it in four pieces. We've all had that. So Matt, Jason, either of you using this in product development? Actually, no. I'm with Sean. In our world, it's borderline useless. Outside of, I think, ideation. So our product team has sort of broken up into there's the weekly design drops. So what else are we putting on the cases? So I think for that, it's been actually really helpful to explore the fringes and edges of interests online. But I think that's less hardcore PD, which Sean is hitting on. But no, like, mechatronics, electrical engineering, all that stuff. No, nobody is genuinely using it in their, I would say like their actual work, right? It's just not good there yet. And Jeff Bezos just raised like a bunch of money to go out there and build like AI model for CAD. So like, maybe this is all coming. But like, yeah, we use it to make a lot of color choices or whatever. My bottom of the list, in number eight, I have operations, number nine, we have leadership and people, number 10, I have product development. I want to talk about operations because it's Mike's number one. And I'm like, how are you getting value out of this? Teach the audience. Well, here's my thought process in putting it number one. In operations, so we're talking about things like fulfilling POs and moving things around with logistics and placing your purchase orders. I mean, I would put inventory and like planning kind of in here, Sean, which probably would change your perspective if you grouped it in there. But it's like, all of the blocking and tackling to keep items on shelves, to keep things in stock. Basically, it's the way I think about and keep and getting product to the customer. And the thing about that is number one, there's really robust digital context basically on all of that stuff at this point. There's APIs, you can get all the information. So you don't have a context deficit. And there's not super intricate judgment going on, usually. Like, there's not a lot of qualitative pieces that you can't teach the AI to have. And so, for example, like inventory and planning, which I know is one you've talked about, like, you can just kind of solve that. Like, hey, here are all my constraints. And here's all the pieces of context. And I want you to come up with a plan. And it's just not hard to move your organization towards the way that we're planning out our inventory, the way that we're placing our purchase orders, the way that we're putting it on ships, the way that we're moving it to 3PLs, the way that we're sending it out to POs to our vendors, is just like clockwork. And it's much more automated. And the reason why I think that's number one is because it has to happen. Like, your business basically dies if it doesn't happen, that there's real money to be saved, and that it removes all of this complexity from running your organization. Like, the more that you can just focus on product and marketing with your organization, those are the growth factors, the better. And it just totally takes operations to much more of like a solved game. So I've been amazed at our team internally, the tools they built, the automation, just in the last few months. We have an internal app builder that we basically have like a context layer. And then on top of that context layer, you can very easily build apps. A lot of the most useful apps have been built by our operations groups. So I'm just very bullish on this. And I think you're just going to be able to run world-class operations with less people. You're going to be able to run a much more inexpensively. You're going to be able to have much more clarity on what's going on in your supply chain at all times. And those are kind of the lifeblood of a business. - I agree with you, Mike. You know, my team in Ops look fulfillment, you know, is a big thing, right? And we are, we're actually trying to, we're constantly trying to take down our percentage, you know, of cogs or percentage of revenue fulfillment cost. And we, we're global. We have many distribution centers. We are having to get stuff in and out of Amazon. You know, we've got many, many, many containers on the water because our products are large. And there's a lot of stuff moving around. And I know that my operations team has found like major, major savings and major, you know, just efficiencies through this, through cloud, through MCP using fulfill to do that. It's been like a huge, these guys aren't for real. Like seriously, these guys are so happy. I love to see it. - Most AI tools right now are all promise and no delivery. You know exactly what I am talking about. Super fancy launch videos. This is why I'm in loving what Rich panel is doing. They have AI and support smashed together, made it practical, made it useful, made it valuable to brands today, not on some future promise. And instead of asking you to spend weeks writing prompts and uploading help docs and babysitting, they flipped the whole script. There AI builds your support team for you and everything it needs. I've watched it, it works, it's freaking amazing. Rich panel even guarantees 50% of your support volume will be automated by AI within 30 days or your money back. I call that a no-brainer offer. The pricing is also kind of wild, about 20 cents per conversation instead of most other vendors being like $1 to $3, which is a little nuts. If you are interested, go to richpanel.com/demo, not for some generic demo, but to actually book a call and watch them build your actual support team. - I didn't think about the inventory planning or buying 'cause once again, I think that is a solved issue. Like inside of your organization, I was even thinking about it as a data problem. But you're right, if that's bucketed under operations, I was thinking I'm like, pickpack and ship and like, how's AI helping you with that, right? - And one of the themes I think that's come up in this conversation is, AI has not punctured the physical world yet and that that is coming. You know, the next phase is going to be when it really gets into the physical world and it really can help in product development and you do have robotics and there is this extension but we're not really there yet. So I would agree with that, Sean. But yeah, I think there's a lot of, I guess one way of thinking about it is, if you say data and reporting is really valuable, it's conjoined twin as operations, right? Because what you're doing with the data and reporting is usually you're turning that into operational decisions and I kind of see them as two sides at the same coin. And I think that that's why I put them one and two is that it's like the information about how we need to, like what we need to actually do and then the doing of those things, if you can use AI to be better in both those camps, like man, you're going to be in great shape. - It has, and the operations thing, like so we run our own factories and we do demand planning for us is almost daily, right? And Claude is now doing that just because we have data warehouse, we have all this stuff. Like we used to, our process was sort of like, our factory managers, whatever that title is, every Monday they would sort of have their own demand plan for the week. It's like, these are the tools we need to run and these quantities and these colors. how we kept the whole Pila like on-demand inventory thing going is we were all kind of always trying to be like a day or two or three ahead on what we thought would be needed right by our various channels. AI is doing that now and it's far more accurate. Our efficiency is actually quite a bit up at a factory level. So I would I would bucket that as Operation Sean but it is like it is like Mike you're right that is more data. It's just that it's capable of processing a lot more information that our team could do it like humans could do it before like it can look at every single order whereas before we would look at like aggregate data because that's how a human would process it right. It's like show me the averages show me the summaries. This thing is looking at like every single order and every single item in real time and making better choices for our for our factories. So I have a take on this and that is that everything in your business will eventually be like a prediction market. The prediction markets are these amazing things that suck in all this information and can say at this given point in time this is the most probable outcome and we've seen that they like are really accurate and like a lot of what we're trying to do with our business like with our you know demand forecasting for example is basically that it's just a really inefficient market that is not doing a very good job of sucking in information and bringing it up to the the second and with these systems you're just going to be able to be like yeah plug into all these data sources and then just give me like as of right at this second what is the best prediction of the future and work around that and our businesses have been anywhere near that agile but that's what's coming. So as as I said earlier my my last one was leadership and people I rank that as my worst I think that talking to Jason if I think about it from a different angle I can see that differently so obviously using AI to manage people is probably terrible don't do that but obviously it's pretty profoundly going to impact the way we think about leadership and people. Here was my ranked list because there's one of these I wanted to call out I know we've discussed as a group a lot. Number one operations two data and reporting three customer service for content creation five internal knowledge base six paid media seven market research eight website and CRO nine product development and 10 leadership and people but guys I know that for each of you I think customer service has been the most transformed to date by AI and it's just really remarkable what we've been able to build internally we have a bot and the just the volume of our tickets it does how quickly it does it you know one of the sponsors of the pod rich panel has unbelievable offerings in this area has that been as true for each of you in your organizations that customer service has been dramatically improved by AI oh my god yes it's not it's freaking insane it just like even just think of it this way even if you didn't have AI that was capable of answering all of the basic questions which it is it can handle like 98% of our tickets it's still going to make all your agents way smarter like you know like you've already said like you can ask it a question or Jason you can ask it a question in seconds it's giving you an answer that applies up and down the org so why wouldn't it impact customer service the same way mean rich panel have a bet that by the end of the year they'll be doing over 30 percent of my tickets with AI and they're getting I think they're there right now right so totally AI topped bottom resolving tickets for us and customers seem to like it more right the the AI chatbot has like a 98% C sat score so like everyone's having a good time talk to the AI chatbot it's because it's just giving the money Sean that's what's happening it's like sending out $100 bills without you really knowing I said I should dive into that maybe I do have a free money bot well I said this before but when we first implemented this the biggest concern is are we gonna be able to nail voice with this AI chatbot and very quickly we're like wow this thing's way better than we thought it's like you said Sean it's getting better C set scores than we would have ever expected sometimes like somebody wrote in about you know like an Oklahoma City Thunder item that we had that was sold out and the AI chatbot noticed that they were writing from California and was like yeah we know it's tough to be a thunder fan you know with all those warriors fans around but we're going to get this back in stock later blah blah I mean it was just like riffing on on things in ways we wouldn't have expected and we actually learned that like the worst part about the this this transition to AI for us was like this this thing had no chill so it would be like somebody would send in a support inquiry and like two seconds later they would get a response and so it was like hey you know what we call it Hally but like Hally you got a chill out you know like we got to give them like a few minutes before you respond and so if that's your biggest problem is it's being too prompt in responding to customers that's a great problem to have I want to talk about AI job displacement for a second you know so it's a American hiring was a curve like this right and like it was it was a steady line on the graph and be with the rollout of AI maybe the curve has inflicted down a little bit so like we're hiring less people than we would in the world without AI but job job opening is still happening I just told you that I'm I'm gonna hire 10 people here right so like there are still new people being hired maybe it's at a less frantic pace than if we didn't have this AI boom or whatever but where that's definitely jobs are being are going to be lost it is you know international CX agents those jobs have already left America right they've they've moved over to the Philippines or whatever else and now those jobs will be totally eliminated by AI so like do not hold Manila real estate is this what I'm saying right now it's like there's well let me divest as we're speaking not investment advice or you know we just talked about how powerful it is with Excel and Mike a top 1% power user hasn't logged in this year right and you know that's going to be very very bad for the knowledge economy of places like India right where big banks have outsourced lots of their you know computing work right their manual data work to India Pakistan wherever and now there's going to do it locally with cloud for probably the same price right it won't be cheaper to use cloud would be the same price but it'll happen instantly so and it'll be a better quality at you know like and you have all your contacts like it's it's an overwhelming value proposition Sean is it an ensuring of productivity is that how you guys look at that like so much productivity was outsourced is that re-insuring where AI is not going to job loss it's just going to shuffle the deck and I think if you want to get hired at a bigger company I think your job prospects in the next 10 years are worse but I think it like you just can see so much more so many more people start ventures at their own you're going to see so many new smaller firms and part of the reason for that is that like if you think 50 years ago it was difficult to compete with the incumbents because they could just do things that you couldn't do right and there's actually a great post Aaron Levy great that's his name right box Aaron they so there's this javans paradox thing and he talks about the evolution of marketing agencies and that basically for a while like you had to go with one of the big boys if you really wanted the best stuff because they had these huge creative departments and you couldn't get the level of creative output if you didn't go with one of the big boys because the scale like created a competitive advantage and that you would have thought that the invent a Photoshop would have lead led to you know less designers but it had the opposite impact it just exploded the number of designers and it made it now where smaller design firms could compete with the really big boys and this is exactly the same case like to have a really great customer support department 15 years ago you know you had to be at whatever size x size now you can be one hundredth of that size and have that same level of customer support because of the tools and all of this faith all this favors small businesses basically and entrepreneurs and new venture creation that I think we have great customer support but you know what you could start a new company tomorrow and probably have a similar level of customer support because the tools that are available and that there's just so much opportunity in that Black Friday cyber money are coming are you ready not in the normal marketing calendar and offers prep sense I am talking measurement and attribution are you even going to know what winning and losing looks like when the big Q4 season hits reality is the businesses that win set up their measurement solution when the times are slow not the night before the big weekend there's a reason for this you see with north beam you're getting a totally independent completely new set of ad performance numbers with infinite lookback windows that means that the longer that the data grows the more valuable becomes so when cpms are spiking in November you will know precisely where every dollar is coming from while your competitors are guessing this is important Black Friday is one in the summer not the day before book a demo with north beams today the link is in the description go check it out Matt asked if it's going to be an on showing of productivity well it depends where they build the data centers because that productivity might might go to space but no I do think the job loss narrative is is is a lie because those jobs have already been lost they've already been shipped out of America right and I definitely agree with Mike that like Facebook will have less employees in ten years and it has today and the company will be way bigger like they're they're going to get hyper like I'm talking about ten million dollars per person at rich they're probably talking about a billion dollars per person or something crazy right I mean they put they they probably won't just because of the real estate investment but like I do think they'll have less people so it's a dichotomy will be bigger it'll be more dynamic and it's going to be a way more smaller firm I believe in that future and where do you guys think? that we're going to be competing as brands. So where is competition going? Six months from now, 12 months from now, 20 from months from now, like I'll give you a bit of a frame on this. I had somebody send me a message on X around creative. You know, in his question with something like, if six months from now, 12 months from now, AI is capable of making video, right? Which is probably going to be in such a way that everybody has the ability to make hundreds or thousands of pieces of creative all at the same time and upload those into ad platforms, is that where is the competitive advantage in getting attention and getting distribution? Like that's kind of the game we're all in, right? It's like, how do we acquire a customer profitably? How do we make our unit economics work? I curious if you guys have any takes on this, because that is, I didn't have a good answer. So, you know, help me. What is your take on this, Sean? Well, my take is, if we're in a world where anybody, so Chinese factories or black ad drop shippers can make any beautiful creative they want, they can impersonate any celebrity they want, and they can put their products in those ads. How do you continue to get sales and transactions? It comes down to, do you have more budget, right? Like, do you have, because what we're forgetting is it's, there's still a delivery mechanism. The delivery mechanism is Facebook ads. And Facebook wants to charge a higher and higher CPA and CPM every single year. And the problem with, you know, this competition coming in is, is will they have everything in place to support a $100 pack, right? And that like the maturity, the reason why you have to lower op-ex to put as much money into ads as possible, right? And like Jason said about lowering cost of shipment to make sure he gets as much money into ads as possible. Is I think we're going into a future where capital is the thing that lets you win, right? Which sucks if you're a new, if you don't have a business and you're listening to this right now, but who's in the consumer space? You know, we're going to a more nationalized system. So that there will be tariff borders going up. It'll be hard to get direct to China shipments coming in. So you have some sort of protected month there. And then just naturally, those people are going to try to win on price. But if you win on price, you can't win on CAC. And I just think we get to a world where there's like a, there's like a, there's a floor price of everything sold on the internet. And it's just going to be higher than you think. Yeah, scale economies and some of the traditional modes, I think are going to come back to mattering. And like one example in our business right now, there's parts of our business from like a little bit concerned about, you know, how competitive forces impact it. And there's other parts where I'm like, I feel great. Perfect example, we're doing, we're embroidering like a thousand units a day to two thousand units somewhere in there right now. And we just bought four more embroidery machines. I think we have something like 12 to 14 embroidery machines. That's just a competitive advantage, right? Like that's literally like you got to have the machines. There's very few people that embroider at scale in the United States. So ones that do often have like one month ship times. And so like that's just an asset that is not easily disrupted by AI. Because it lives in the physical world. And actually what I'm thinking about is how do I do more embroidery? Like I've got this competitive advantage. How do I spin up more businesses around it? But you're going to need to be thinking that way. I think Matt is that like some of the things that were really helpful in the last 10 years won't be in the next 10 years. And then the one other thing I'd say is like, I think brands can be harder than ever to build. And I think it's going to be more valuable than ever. I mean, brand is the ultimate equalizer that somebody else is selling. Yeah, it's like, I mean, everybody can go and build a water bottle. He'll Sean did it, you know? I'm just kidding. I wouldn't cut that up. But like anybody can go and order a water bottle from one of any really good manufacturers. And so like I said this to my team before, if this means something, if this SM at the bottom means something, really bright future, and if it doesn't, we're screwed. We'll eventually go out of business, the end, you know? And so like brand building is going to, like e-commerce, it kind of bifurcates into, you've got kind of drop shipping, kind of like, what is the opportunity of the moment? Hit it and get as much money as you can really quick. That'll always be there. But if you're like talking about enterprise value creation, it's got to be brand, right? And I think we should do a whole episode about me and last from water bottles because I would recommend absolutely nobody do it right now. It's like, it's like, how are you going to stand out? It's the craziest market on earth. Like, you know, my microchairs, it's a knife fight. But Ridge can do it because it has people showing up every day on its website. It has some sort of attention already. We've been talking about use cases with AI. We ranked a list and you're probably wondering, hey, where did you get the list from? Well, actually what we did is we took the operator's knowledge base, which you can go to. It is now online. We will leave the link in the show notes. And it literally has cataloged everything we've had on this podcast, everything you've heard on mobs and any of the other operator's properties. It is incredible knowledge base where you can go and say, hey, I'm wanting to know like, what did the operator said about this or that? And you can immediately pull all the quotes, look at everything we've said over the years. It's insanely helpful at it. Advise you take a look at it. But we went there and we just said, what are the top 10 things we've talked about when it comes to AI? That's how we got the list. That's what we ranked today. Find ways to apply AI. You're going to drive more value. Keep coming back to the operator's podcast. We love having you with us. And we will see you next time.