Turning AI Hype into Store Ops: Manda Miller & Mariya Zorotovich (Toshiba & Intel)

(Maria Zorotovich at 00:00:00) Most of the successful retailers that are gonna start to push ahead are thinking holistically.

(Amanda Miller at 00:00:06) So I think the difference between AI theater and something that changes the P&L, right, is all about can that particular solution actually work in the real retail store, in the real retail environment?

(Joel Beasley at 00:00:27) So just to start out at the beginning, I want to understand what both of you do.

(Amanda Miller at 00:00:33) I guess I can go first. So I'm Amanda Miller. I'm on the Strategy and Business Development team at Toshiba Global Commerce Solutions. I'm on the strategy team, and a lot of what I do is just market research. I look at what retailers are investing in. I try to understand where our competitors are going, their movements. I look at customer needs, and I try to kind of triangulate all of that together to help inform our business of what we should invest in, how we should be helping our retailers, and how we should be showing up for the industry. Maria?

(Maria Zorotovich at 00:01:07) Yes. So I'm Maria Zorotovich. I lead consumer industries at Intel, and my organization is focused on development and expansion of advanced computing solutions across retail, grocery, hospitality, venues, retail banking. So we get to work across the ecosystem partners like Toshiba to go and define new solutions that apply emerging technologies and edge computing in really practical ways to deliver better customer experiences.

(Joel Beasley at 00:01:34) And so you both work together on a day to day? You're actually the representative for each company that comes together? What does that look like on a day to day?

(Maria Zorotovich at 00:01:42) Well, for me with Toshiba, Intel has a very long-term relationship with Toshiba. And what I love about what Amanda's work drives in the research is that we bring together different perspectives and insights for what's happening in retail or in grocery or convenience, and we come together to find a common problem to go solve. Right now, we're highly focused within the commerce space and how we improve that checkout experience for our customers through a myriad of different solutions. And so we kind of bring the best of both worlds together. From an Intel perspective, we're trying to look ahead at how do we power those types of solutions. And I think with Toshiba, they're really kind of that touch point to the customer. So what is that device? What does that solution look like? How does it operate within a retail ecosystem, or a retail store I should say? And so that's where we come together, kind of bringing that power about the customer and the insight and solving.

(Joel Beasley at 00:02:40) How long have you both been working together?

(Amanda Miller at 00:02:42) I've been at Toshiba—next year will be my tenth year. So almost a decade for me.

(Joel Beasley at 00:02:47) So you've been seeing what's been transitioning with the customers for quite a while.

(Amanda Miller at 00:02:52) Yeah, definitely.

(Joel Beasley at 00:02:53) What's the big thing that's happened recently? What are they all asking for and looking at now?

(Amanda Miller at 00:02:58) I think from my perspective, what we're seeing from our retail customers and just the industry in general is there was kind of this big push and question around what is the practicality of AI. And a lot of the questions I get from retailers and client briefings is who's really using this, how is it helping them, what problems is it solving, and how did they implement it so that it could solve those problems. Being in strategy, a lot of the questions are typically around P&L, right? So revenue and margin protection, where is that gonna hit, and what does success look like from that viewpoint? Those are the questions that we're getting now. What is the real practicality of some of these technologies that we're seeing a lot of, particularly around AI and agentic AI?

(Joel Beasley at 00:03:48) How do you begin to answer that?

(Amanda Miller at 00:03:49) I think it has to start with the problem, right, and understanding what the retailer has already built. So I like to try to think of it as, you know, when you go into a store over the last ten years, the one thing that has stayed the same is a customer wants to have a good experience there, whether it be convenience or whether it be the thing you're looking for is there, whether if you're looking for help. Right? All of those things are the same, like what makes a good retailer a good retailer. Technologies should enhance that and scale that, right, to a much broader customer base. But it shouldn't take away or distract from those things that make that retailer shine in the retail industry. And so we start to answer that around—we don't want to introduce risk to those things that have made that retailer successful. And we don't want to introduce risk to making the customer feel something other than delight when they go into the store. Right? So we look at it from that perspective. And then what outcome are you trying to achieve? What problem are you trying to solve? And making sure that we solve it in the right way. If AI is the answer, great. And sometimes it's not. And so we try to kind of help them navigate what is the correct way to solve this problem.

(Maria Zorotovich at 00:05:16) And maybe, Joel, if I could add to that, because I love where Amanda is talking about delighting the customer, creating a great experience, and figuring out how to go and solve that. The next layer that I often hear from retailers is about how do we operationalize AI as really a core operating capability across the organization where we're moving into execution, and we're doing that consistently at scale. So the challenge is starting to move beyond the conversation of adoption into execution. And that's really where the value and differentiator comes into play between different retailers. Those that can truly integrate and have a plan around AI as a capability to impact decisions, workflow, accountability, and execution at the end of the day. Those are the retailers that are going to start to evolve pretty quickly in how they operate and how they can serve up an improved experience.

(Joel Beasley at 00:06:12) Do you meet with the retailers as well, or is it just like Amanda meeting with them and then relaying information? How does that work?

(Amanda Miller at 00:06:18) I think it's two-sided.

(Maria Zorotovich at 00:06:19) And I think this is why the relationship and collaboration work, because for Intel, we sit at a different place in the value chain from where Toshiba sits. And so we work across a number of different value chain players that are contributing into the greater ecosystem along with the end customers or brands retailers. And so we help to bring those insights into play to help understand, you know, through our shared outcomes together, how we can go solve those problems.

(Joel Beasley at 00:06:50) What's the current retail trend that's being overhyped right now? Are there any?

(Amanda Miller at 00:06:54) I have my own personal feeling about this.

(Joel Beasley at 00:06:56) That's what we do here.

(Amanda Miller at 00:06:58) That's not a Toshiba feeling.

(Joel Beasley at 00:06:59) It's okay. We can differentiate between the two.

(Amanda Miller at 00:07:01) I think the overhype—I'm kind of tired of the whole conversational AI chatbot. I think there's a place for that, and I think there's a time where it will all work, right? But a lot of my experience with it is it's just not quite human enough for me. Right? I kind of still feel like, alright, I'm still talking to a machine, and I'm gonna have to figure out how to get in touch with a person because it's not answering my question. Right? And so I think it's kind of a little overhyped from that perspective. I think it was an easy point for people to start at, and I think it was kind of easy to operationalize. But I'm starting to think, did it create a little bit more frustration than value? And how do we solve for that problem, right, so that we can start to really get true value from it. So I think it's a little overhyped for me.

(Maria Zorotovich at 00:07:51) I think that one resonates a lot with me. I think definitely it was probably an easy type of use case to pin different technology terminology around and kind of move that one to the forefront because it was so evident and tangible in terms of AI. But I completely agree in terms of its overall value to move forward. I think there are moments for sure, but truly holistically end to end, I think people are still trying to figure that one out.

(Joel Beasley at 00:08:20) I have a new idea. Every grocery store should be laid out the same way. Every Home Depot should be identical no matter where you are. All these stores, they have the same brand, but you go inside and they're all set up differently. As a consumer, it's gotta be the most frustrating thing in the world.

(Maria Zorotovich at 00:08:37) You know, who doesn't want to have a little bit of their own brand touch on their physical environment? But I get it, Joel.

(Amanda Miller at 00:08:44) I hear what you're saying.

(Joel Beasley at 00:08:45) Come on. As a consumer, you would prefer if you walked into a grocery store called XYZ and you do it in Florida and then you do it in New York, wouldn't you prefer it to be laid out the exact same way? And we know where everything is.

(Maria Zorotovich at 00:08:58) I may have an affinity to the same brand or same chain that I know and love to maybe have some similarities in how it's laid out, but not necessarily from brand to brand to brand or from one chain to another chain.

(Joel Beasley at 00:09:17) I'm talking intra-chain. I'm talking like if it has the XYZ logo, the internal layout. I'm not trying to be a dictator here and saying—

(Amanda Miller at 00:09:25) How to do—

(Joel Beasley at 00:09:26) —that to do business in America, you have to follow this floor plan. I'm just saying if I like a specific grocery store, okay? And it's always rearranged differently. I travel for work, so I fly once a week. You know? And that [product], it's always in a different spot. And I'm like, just put it—I just wish it was always in the same spot.

(Maria Zorotovich at 00:09:45) Fair enough.

(Amanda Miller at 00:09:46) Yeah. Ask the customer all the time.

(Joel Beasley at 00:09:49) Exactly. This episode is—they're fielding a real complaint that Intel and everyone's gonna get together, and they're gonna solve for me. So now just curious just so I can close the loop in my brain. The chatbot thing being overhyped, I get it in a general sense. Is that happening in retail? How is that happening in retail at all, the chatbot?

(Amanda Miller at 00:10:09) Yeah. I mean, I think so. I've used chatbots with retailers, right, where it's obvious that you're chatting with a chatbot. Inevitably, it always asks me, would you like to talk with a real person? And I'm like, yes please, because you're not answering what I'm asking for.

(Joel Beasley at 00:10:28) Have you ever had a great chatbot experience?

(Amanda Miller at 00:10:31) If it's a straightforward ask, right? Like, if I need a refund or if I need to make a return or something like that. Sometimes if it's straightforward, yeah, it's okay. It's very transactional, though. Like, it has to be a very set transactional use case that I'm going on there for. I don't think where it's quite there yet is if it's making recommendations or it's trying to glean information for me to make a better recommendation or something around what I should purchase. I think that is where it's starting to fall a little bit short.

(Joel Beasley at 00:11:07) Yeah. I've only had one awesome experience with a chatbot, and it was a refund situation where I was able to get through the entire refund process in like ten seconds. And it validated me, validated the transaction, did the refund, and everything was good. And that only happened in the past month. So if all the chatbot—here's my experience with the chatbot, probably same as you, Amanda. I go to ask—I research, do all my own research to figure out. I can't figure out the answer or I know what the problem is. I need to talk to the person, and I go to it and it can't do what I want it to do. And I just have to—yeah. That's so frustrating. We're gonna work on that too after the episode. We're gonna solve the world's problems today. So what is the next phase of retail innovation? What can businesses actually execute today that's really interesting?

(Amanda Miller at 00:11:55) I think retailers have been really good at keeping up with technology and emerging technology and how it's useful in their stores, right? So when I first started at Toshiba, it was all about e-commerce, right? And then we moved into, well, things need to be more omnichannel. And then it was like, well, we gotta figure out our fulfillment. We gotta do inventory. How do we deal with retail media, right? And then there's all this computer vision. I think retailers are pretty good at getting technologies into their stores and into use cases and out of proof of concept. What I think is kind of the underlying issue with all of these new capabilities and all of these new technologies—there's still no kind of underlying layer that connects all of them. And so I think that's the data, right? I would love to get Maria's take on that. But when I started, when I got out of business school over a decade ago, right, we were talking about big data and how it was gonna change the world. We still have a data problem, right? It's still not clean. It's still sometimes not reliable. It's not necessarily trustworthy data that you want to be popping into some of these newer technologies and utilizing it to run those technologies. So I think retailers are really great at trying out technologies and getting them in the store and finding use cases for them. I think combining them and executing them in a way that's good for their business and good for their customers is still a little bit lagging.

(Maria Zorotovich at 00:13:28) I think that most of the successful retailers that are gonna start to push ahead are thinking holistically, looking across all of their stores, looking across their entire infrastructure and backbone, and thinking about how do we continue to evolve in an environment where we don't necessarily know the new and exciting experience that's going to be thought of, but we are truly creating a backbone that is going to allow for decision dexterity and quick actions for really fast decision making. You know, setting the stage for what AI and agentic workflows can actually do for a business when it comes to truly changing how they operate. And that's where I see some of the conversations going truly from a, is it cloud? Is it hybrid? Is it near edge? Is it far edge? It's all of those things, right? Those don't compete. There are certain reasons why we have and what we need at a far edge versus near edge versus hybrid and cloud in terms of data. You know, where does data come into the organization? Where is it stored? Where is it modeled? Where is it pushed back out into different applications? How is it used in the instance when working with the customer that's right in front of the associate in the store? I think all of those things are coming into play and matter because, you know, the organization is connected by data. There's governance and there's workflows. These are the types of conversations taking place where organizations are gonna truly start to move ahead on how they evolve that experience and how they operate overall.

(Joel Beasley at 00:15:10) So between Toshiba and Intel, you guys are focused on moving AI pilots into the real world. Is that correct?

(Maria Zorotovich at 00:15:18) Yes. Absolutely.

(Joel Beasley at 00:15:18) Can you tell us about a project that you're doing, putting out there into the real world right now?

(Amanda Miller at 00:15:23) So where I sit, I can't exactly share—

(Maria Zorotovich at 00:15:26) A customer name, but let me give an instance of that. I think every day when we're working with our partner, Toshiba, we are thinking about, again, how are we reducing friction and improving that checkout experience? Because every single matter counts. This is in addition to the actual brand or end retailer, what type of format, what type of physical experience they want to be able to give their customer that's coming through and doing checkout. And so we're working together on creating those moments that'll come into a store and working through proof of concepts to really validate the direction and the all-up experience. So not just the technology feasibility, but how does it resonate with the customer?

(Maria Zorotovich at 00:16:11) How does it net in the operations and the experience within the business and getting that feedback and fine-tuning and continuing to then roll out at scale? And that's one thing I would say between our partnership at Intel and Toshiba. We have operated many years at moving solutions into scale across many doors, many touch points in retail, and that's been proven given where Toshiba is currently serving. Amanda, what other thoughts there?

(Amanda Miller at 00:16:42) Yeah. I think we work really great together just because we're thinking about not isolated capabilities. So Toshiba and especially in my role, right, I'm all about the store and store execution. Right? It's not about how do I execute isolated capabilities across the store, but how do I bring that all together and really have a kind of a continuous connected store execution capability where signals are coming from everywhere.

(Amanda Miller at 00:17:12) Right? If you're gonna have signals following people around and where they're walking, right, they have to be able to do something for you that makes your business better, that makes the experience better. Right? So really understanding how can we make the store more about driving action from the signals that we're creating from our solutions. Right?

(Amanda Miller at 00:17:34) And how can we partner with companies like Intel to kind of help us drive that from an edge capability perspective?

(Maria Zorotovich at 00:17:42) And this is where AI is truly becoming this connective tissue that's helping to bring together the actual physical in-store experience with customer intent, the workflows to serve that customer, and actual physical execution in a retail environment. And that commerce orchestration to inventory to labor allocation to, you know, service, all of those pieces start to come together, and that's where Toshiba and Intel are very intently focused on continuing to reduce that friction and evolve the experience for the retailer.

(Joel Beasley at 00:18:18) Is there any AI pilot, a project that you're specifically putting into the world right now that you want to talk about?

(Amanda Miller at 00:18:25) So I'll be very honest with you. I don't build projects. Right? I said I'm in strategy, but I do work on the front end part of that. Right? So a lot of the things that I'm working on and trying to educate the business on and kind of the people who are building our solutions is the why. Why should we be able to seamlessly connect to the back office ERP? Why should we be able to seamlessly connect to whatever is happening on the front end with consumer AI? Right. I'm trying to bridge the gap between what they're working on and the why that I'm seeing in the industry and the market so that they can then go and say, alright, I understand why I have to do this. So let's build this really great AI solution around, for example, produce recognition for Toshiba or loss prevention around shrink in stores. Those things are driven by the fact that we saw a clear problem in the market, and we saw a clear operational issue in the store around those areas. And so a lot of what I'm doing is kind of setting the groundwork for the building, for the reason why we should probably start to help our retailers solve whatever it is that I'm seeing trending in the industry.

(Maria Zorotovich at 00:19:41) So here's what I will say. So at NRF this year, NRF 2026, Toshiba and Intel spoke about modularity and the importance of modularity of different types of solutions. And the reason we talked about that is because the landscape continues to change. And what I mean by that is as new use cases start to emerge with the technology and capabilities of AI, completely able to shift entire workflows or gather data in new ways or provide insights or help systems take actions, that starts to shift the landscape in terms of how you look at your compute, how you look at your hardware, how you manage that over life cycles. And so modularity is an important thing when you think about technology, different components, and interchangeable parts. And so this is an area that Toshiba and Intel continue to talk about and continue to try to figure out how do we go solve that challenge for retailers, particularly in the tech teams? They have to go manage this technology on the floor and continue to make it easier for them.

(Joel Beasley at 00:20:53) So what is the real difference between AI theater and AI that changes a P&L?

(Amanda Miller at 00:20:58) So for me, right, I go to NRF. That's the yearly conference that a lot of people in the retail industry go to every year. And you go into booths, right, and you see a lot of demos around AI, and they work really well in a very controlled setting. Right? So I think the difference between AI theater and something that changes the P&L, right, is all about can that particular solution actually work in the real retail store, in the real retail environment where you've got a lot of things going on, quite frankly, that you can't control for. And that actually kind of pushes that solution now from theater to the P&L because now you have to have an outcome there, and it has to be directly tied to your operations and your business model, right, to either, A, help you grow your business, or, B, at least protect your margin from whatever problem it is that you're trying to solve. So theater, great in a controlled setting. If you really want a good outcome, it's gotta be able to go in one of the most chaotic environments, and that is retail.

(Maria Zorotovich at 00:22:09) Totally agree. Completely agree. AI, to change the P&L or have an impact there, it truly has to have operational value. Right? It improves the business outcome, a true business outcome, not just a technology outcome around AI usage, but truly having an impact on improving faster fulfillment, better merchandise availability, lower shrink, improved service, something that truly is a marker of success within the business and is success with the customer.

(Joel Beasley at 00:22:40) Does this connect at all back to the restaurant reservation example?

(Amanda Miller at 00:22:46) It does. It does. I can go through the, yeah. So I was working on a new kind of concept that I wanted to share with some of our clients at our client briefings. And it had to do a lot with orchestration of capabilities and being able to bring AI into the real world and what that really looks like and what we were seeing in the market other retailers were doing. In my particular example, a couple of months ago, I was really busy. My kids were like, I'm hungry. We gotta go out to eat. So I opened up my phone, and I Googled a restaurant. And Gemini popped up and said, do you want me to make a reservation for you at this restaurant? And it said at the top that it was gonna call the restaurant. It was gonna do all the things. And I was like, okay, yeah, I'll play this game. Right? And so I said reservation for four and around six. And off it went. Right? Came back maybe about five minutes later and said, you're all set. Here's the restaurant, and here's the time you show up, 6:00. And I thought, that's interesting. Right? And that really got me thinking about kind of this concept of agentic commerce and agentic consumer-facing AI. Right? Because at that point, it had taken kind of what I would normally do in researching and trying to do all that manual stuff myself and make the reservation. Right? It took it out of my hands and went and did it, right, and made a promise to me. It said, your table is available, and it will be ready at 6 PM when you show up to this place. And I kind of thought, you know, there's this whole concept of AI is like the new front door, which I really kind of hate buzzwords, but because I really immediately thought, but now you've just changed everything behind that door that now has to go right operationally to deliver on that promise. And so when I show up at the restaurant as a person, as a patron, my table still has to be ready. Right? They still have to have timing correct in the kitchen so that my food is prepared and on time. Right? They still have to provide a wonderful experience and ambiance. Right? My hostess still has to know that I'm gonna be there. The reservation has to show up. And I pretty much trusted that all of that had happened without me actually doing the manual work to get it there. So I think the whole premise of agentic AI and how AI theater versus what the outcome is. Right? There's always some sort of back behind that front door outcome that you have to plan for. And so AI theater kind of makes the promise. Right? But, you know, the store and the restaurant are the ones that are still having to keep it. And so I think that's kind of the concept of theater versus outcome. Everything has to work in tandem for it to be a good outcome, and it has to work for you as a business, and it has to work for you for the consumer as well.

(Joel Beasley at 00:25:39) And did both of you go to NRF?

(Amanda Miller at 00:25:40) I believe so. Yes. I think so.

(Joel Beasley at 00:25:42) How was it? Was it good?

(Maria Zorotovich at 00:25:43) It was good. I think from my point of view, lots of energy. Lots of energy on the floor. And, typically, there will be a headliner in terms of a tech topic. AI, of course. Gen AI was one of those headliners. But what I found really interesting was the conversation wasn't just focused on kind of the front end use cases. There was definitely a healthy amount of conversation around infrastructure, long-term supportability, how do we actually manage in an environment with more AI? So I'll just say a much more holistic conversation end to end to truly enable AI as a capability within our organization. And that was pretty exciting to see that people are thinking more deeply about this technology and what it means for their business.

(Joel Beasley at 00:26:37) I also was reviewing the prep notes from the meeting before the call, and you had, Amanda, you had noticed AI splitting into store ops AI versus consumer personalization AI. Was that one of your takeaways from NRF as well?

(Amanda Miller at 00:26:50) Yeah. So I did kind of see when I walked into booths, vendors, people within and companies within the industry either had kind of a focus on consumer-facing front end AI or operational kind of back end AI. So from Toshiba's perspective, right, we're very operational. We're in the stores. We're helping, kind of these tools and these solutions are helping drive operational value. But I still think those two things can't operate independently. I think they have to be very much in sync, integrated with each other because the consumer expects it to be. And so if the consumer expects things to be in sync and reliable and they have confidence in the retailer, then those two things have to be in sync and they have to be, you know, the gaps have to be filled between the two, either with partners or within the same organization.

(Maria Zorotovich at 00:27:52) And I think that goes back to your restaurant example. Right? You may have started within one channel, which was digital through your phone, but that experience had to carry on into a physical environment where you were going to the restaurant or you're ordering. And so I think that's a really good example about the shifts that are going to take place within retail, where today we own things so functionally, meaning very deep and narrow, because that's where we have expertise. But when we look at the customer experience, it actually goes horizontally across many different functions that have to work hand in hand to deliver that great experience across a digital channel into a physical channel and vice versa and bouncing back and forth. And so that's where it starts to get exciting. And so being that the conversation has both a customer-facing kind of AI application use case, but also operationalizing it, you know, being that both sides are equally having those conversations, you know those pieces are gonna start to come together. Retailers that can bring those pieces together faster will deliver that better end to end and will win with the customer.

(Amanda Miller at 00:28:59) Yeah. I think it's kind of like omnichannel but on steroids. You know? It's much greater than that now at this point.

(Maria Zorotovich at 00:29:06) Faster. Yes. And faster. Yeah.

(Joel Beasley at 00:29:09) You got so much technology. You got the cloud intelligence. You've got the edge execution. You've got all of these things happening at the same time. It's a pretty exciting time to be alive, isn't it?

(Maria Zorotovich at 00:29:19) I think it's that next. Right? And I think maybe, gosh, few years back, right, we were talking about data, big data and the cloud, what it enabled. And then we kind of went through all these different phases, and now we're here at AI and looking at, you know, agentic AI and what it can mean for an organization to truly evolve. So it is exciting times. I think we're gonna see an evolution on experience and evolution on business models too.

(Joel Beasley at 00:29:46) You both seem pretty intelligent on the concept of strategy. And so I'm curious, what are you advising retailers for long-term strategy? What should they be thinking about? What should be priority number one right now?

(Maria Zorotovich at 00:29:59) I think for my interaction with retail leaders, regardless of where they're focused in supporting the organization, when we look at technologies like AI, you know, my piece is AI shouldn't just be a feature set. AI is truly a capability across the organization. The goal is not automation. The goal is truly about faster decision making and actions to go deliver the company's strategy. And that delivers results that wins with customers. So stepping back, thinking more holistically about the position on AI as a capability, how do you actually bring together all the pieces to go drive that faster decision and actions within the organization? That's one of the biggest challenges. Again, it's let alone the technology itself and how you bring it into an organization and truly leverage and manage it and have the skill sets around it. But you also have to start to shift culturally around the trust on data and the output of that AI and the trust on the signals it's driving and the next actions for it to truly permeate throughout the organization and drive change.

(Joel Beasley at 00:31:12) Amanda, what tip or insight can you give the audience for them to be able to spend their technology budget in a more mature way?

(Amanda Miller at 00:31:19) Well, you know, I think Maria was right on this because it's all about decision making, and strategy is about decisions. Right? You have to make decisions. That's why strategy exists. And so when you're looking at budgets and trying to make investment decisions on things, which is typically what strategy does within an organization, you're looking at outcomes. What outcomes do I want to drive? What problems do I want to solve that I know are going to be positive changes for my business, my retail business, whatever business that I'm in? And if the technology that I'm implementing is allowing me to make a better, faster, more confident decision, right, then that should be the budget and investment you make for the technologies that you're evaluating. Which one's gonna help me make a faster decision that I can confidently say is going to be something that positively impacts the outcome I'm trying to impact? So you have to give and take.

(Amanda Miller at 00:32:25) Right? So I only have a finite number of resources. I've gotta make a decision about what I'm gonna invest in with my budget, and it's looking at what are the outcomes that are gonna provide me with more benefit and value, and then what are the things I have to put in place to get to that benefit and value. And if it's AI, great. If it's another technology, great.

(Amanda Miller at 00:32:46) But you've gotta understand and start from the outcome that you want and then work your way back.

(Maria Zorotovich at 00:32:51) One question I try to post to people that are seeking pilot or funding investment: what operational capability are we trying to build? And the reason why I try to position it like that is, with emerging capabilities and technology like AI, it is one of those technologies that over time continues to help accelerate the speed in which an organization can operate. So the investment made today is gonna pay off down the road, and it's going to continue to evolve and build upon itself. And so starting to do that slight shift from the actual problem being solved to thinking bigger and broader around a capability that's going to be brought into the organization, I think will help organizations open up the conversation and think more long-term on strategy versus just what is needed in the moment.

(Joel Beasley at 00:33:44) What is the most futuristic thing that you guys are working on? Like, something I could go into the store and see?

(Maria Zorotovich at 00:33:50) I was gonna say, again, without revealing areas where we go and focus, what I find very interesting—and we have looked ahead in this area because where I sit in Intel, I have many sister cohort organizations across multiple industries, and so we always like to share notes and we like to look at what's coming—but in terms of the more, you know, within the next eighteen months, our biggest conversation right now that we're trying to go solve for, again, may not necessarily feel futuristic, but it is so critical for the evolution of service, is truly understanding and treating our retail environments as compute environments and how we evolve our thinking on how we plan and manage for that compute to go power whatever amazing experiences retailers are gonna think of and wanna bring in in a moment to go deliver to their customers.

(Joel Beasley at 00:34:52) And as we start to wrap up, I like to end on some leadership advice. So I'm gonna ask both of you the same question. Amanda, I will start with you. What is one piece of leadership advice that you received, you put into practice, and it stayed with you for quite a while?

(Amanda Miller at 00:35:06) A few years ago here at Toshiba, the leader has since retired, but they gave an informal managerial education session to people in the know, right? New managers. They kinda called them in, and it was a very informal session. But the one thing that this person told me that stood out and I've remembered for a lot of years and I put into practice was: you shouldn't approach people or new people with "trust has to be earned." Trust should be given from the outset.

(Amanda Miller at 00:35:36) And when you have that mutual trust, right, that means you can work together. You can roll up your sleeves. You can do a lot of innovative things together because you start with the relationship of trust. Like, that trust is only broken if they give you a reason to break it, right? Otherwise, the default is trust. And I've kind of carried that through in my own leadership and managerial position as well. And I think it resonates too with retail because, like, for me, retail is about trust, right? Consumers are trusting you.

(Amanda Miller at 00:36:08) They're defaulting trust. So the last thing you wanna do is kind of break that. And once you do, it's really hard to repair it. I think that would be the one piece of advice that I actually took to heart personally. And then, you know, I was able to kind of apply it to many facets of my life professionally and beyond.

(Maria Zorotovich at 00:36:27) And that is such a great lesson to take with us. I think giving trust is really important today. In addition, you know, during times of change, which I think all of us continue to go through—change continues to speed up—change leadership is a critical skill. And helping people gain clarity on the outcome by understanding the why behind it, the destination, and the guardrails, to me, are critical for any success for anyone. And more than ever, with the speed and rate of change that's taking place within many industries and many functions within an organization, that change leadership to help people understand the why, the destination, and the guardrails will help everybody transition faster to, again, go run the business at retail and deliver a great experience.

(Joel Beasley at 00:37:23) I love it. We made a podcast. How do you feel?

(Maria Zorotovich at 00:37:26) Thank you, Joel. Yeah, yeah. Appreciate the time. How was it for you?

(Joel Beasley at 00:37:32) Thank you so much for listening. And if you found this episode useful, please share it with a friend or colleague who you think would get value from it. And if you have topics that you'd like to hear discussed on the podcast, either add me on LinkedIn or send me an email: [email protected]. Every time I get an email or LinkedIn message, it absolutely makes my day and inspires me to keep going.