AI in Retail: How Executives Are Embedding AI

I think AI is going to be a capability, it's going to be an enabler that is going to be embedded in everything you do. Hello and welcome to the Retail Podcast. We are now into the post NRF retail podcast guests that I couldn't get together with at NRF just due to the sheer volume for for for the guests as well as myself. Jane Chung is one of such guests the from the IBM Institute.

Sorry, the I'll start. Well, actually we could keep it from IBM, the institute business value part of our game, which is ultimately the thought leadership and the research and they had some research they had a quick look at I think it came out it was just before or during NRF. But rather than me butcher all of the details about the research, Jane, what give us an give us a view of what you do within IBM or the IBV and then what is the research that we're going to be talking about? Sure.

Thank you. Thank you, Alex. It's a pleasure to be here. You know, like you said, it's post NRF, although it feels like long ago, but it's only a couple weeks ago. So thank you for inviting me to have a chat about the research. My role within the Institute of Business Value, which is part of IBM, is to work with the key stakeholder within IBM to determine the research agenda

every year. So every other year we work on a global consumer research study and then every and then the other every other year we work on executive research study. So I launched the latest IBB consumer research study a few days before NRF, so on January 8th. And no surprise is, is about AI, but it's, it's a research based on five that based on 5000 executive who, who are responsible of AI initiative. So we do have a screening process for people who participate.

We want to make sure that the executive, the leaders of our

participants, not only are they knowledgeable, but they actually are responsible of AI initiative. This year's study is very broad. We talked to we interviewed executive across 13 different area, Alex. So is from the front end of the house, which is customer experience stores to product design, product development, merchandising, inventory management to supply chain operation and then also the corporate function like HR, finance and IT. So very rich study.

One of the challenge is so much data, but to actually drive insight that really matters. So that's, that's what, that's what the study is is about. I'm already fascinated. First question, It's not one that I send you. What's the one? Yeah, let's go. What's the one? Because I, I, I mean, what's the one thing that surprised you? Because you've got a fantastic pool of people to, to, to have data and you've got data coming

from every angle. What, what was the one thing that you thought, oh wow, what's the oh wow piece of data? It's. So I've I worked in retail for 30 years. So between in the industry as a consultant and now with the doing research. What surprised me the most with this study is how uniform and we're talking about data and I love data, how uniform the data are across all area. So for example, you know, I started working in retail in the 90s. I remember Y2K. So there is the E com wave,

right? So it's the E com and then E com is really about the front, the selling of it, of the, of the products, right? And then there's the mobile commerce, social commerce. So then the anchor is always around selling the product, not that the back end is not important, not that operation is not important. And then you know, COVID hit the world and then also by supply

chain disruption. So then the supply chain inventory become really, really critical and everybody become more, you have to be digital, right? And I think that just shifted everybody's behaviour. So then it's OK. How do you engage with consumer and how do you get the product? This always seems like a dominant area where we need to focus on this year. I keep going back to look at the data. Initially it's like, am I seeing the right number, big number

across all areas. So, you know, if you look at the report, we're talking about organisation that are expanding the use of AI and across 14 area almost the same unison like right, right. So very big number between 80 to 90%. That means everybody is expanding the use of AI. And then it's like, OK, what do you oh, you know, where's the focus, where's the trend? So that was the big surprise initially when I just look at the number, well, when I think about it, does that make sense?

Yeah. So that's quite interesting then is that mean? So it has it moved away from AI,

evolve it's evolving role in retail as a tool or because obviously first you do some experimentation, then you look at your business process and you know, how do I optimise the business process and put AI as part of that optimization. So what do you, what's the research showing? Are people actually integrating AI?

What is the evolving role of AI? That's a very good question, Alex. So if you think about it, if just look at it and that helps us like at the end, we took a step back and, and we, we decided on the title, which is embedding AI in your brand's DNAAI is going to be embedded in everything you do. It's almost like, it's almost like the Internet without even knowing it, you will be using AI. The reason why I said that is because not only our company consciously making investments.

So if you look at the budget, we talk about the budget, right? AI as a budget as a best part of the IT budget as part of the technology tool. What we're seeing is the growth of AI spend actually is higher in the line of business. So, so then I talked to a lot of our leaders who are working with our client. We have partners like Microsoft is a partner of ours, Adobe is a partner of ours and our partners, all these solution are have AI embedded in it.

So whether you know it or not, you're going to be using AI, right? So, so AI is going to be embedded in everything we do, just like everyone knows how to Google. If you want to find something, it's going to be Google. But here now is you will be able to get richer in like a Gemini, right? Like you will be able to get richer information. It's almost like it has expanded your search capability and it has offered your capability using ChatGPT.

Students are using it, right, in summarising knowledge, in augmenting knowledge. So I think AI is going to be a capability. It's going to be an enabler that is going to be embedded in everything you do. Yeah, I, I want 100% agree with that. And, and in the sense that most of the SAS providers have now got an AI bot as the interface at once or they've got one or they're building 1 or there's one in, in beta that basically you don't go to the to the software anymore, You go to the

agent. And I think even ChatGPT has released an agent. What's it called? Automation, I can't remember. It was only released a couple of days ago that basically it goes off as an agent and helps you in the real world, I don't know, buy flowers and, and stuff like that. So I, I can definitely see that when you look at your research for retailers and in what areas, because everyone, you know, I think the, the statistics are 52% projected increase in spending AI.

What are those applications retailers are thinking about? I think this links to the first question that you said that surprised you that they're all the same. What? But what parts of the business are they? Yeah, so that's a very good question because after I got I, I was preparing to talk to you. I actually went to look at the details and it's very uniform.

What I mean by that is, you know, on and on average, when you look at the aggregate of average, you look at the AI spend outside of IT was 52% increase. When I look through the 13 different area, the percentage is within 5%, meaning it's about 45% in some area, like in some area is a little bit over 52%. So the the deviation of this is is very close. So it's it's a little bit hard to say which area is is going to be more important in in a in AI

application. Very. Yeah. So you didn't get that because again, you were saying, you know, whether it goes into supply chain or marketing or customer experience, you don't have a sense of which one will get the lion's share of investment from your research. No, no.

And, and one of the one of you know, you think about the data and one of we always provide an, an action guide, right? So one of the important, important action guy that retailers, brands and retailers, vertical retailers too, they need to decide what is the most important priority because obviously AI is a capability that can do everything. Yeah. So what's your core, what's what's the most important for you? And you also need to balance the investment versus return of

investment, right. So you really need to, I think it's highly adaptable, it's a good way. But then you also need to think about the way can it give you the most in ROI? And then what's your brand DNA? So for example, I used to work for Nike and Nike is all about performance. So any product that they produce, it has to enhance the athlete performance. So if you know that, then guess what product is very important. Even though they even though they have stores, right?

They have flagship. So when I work at 90, Nike in the 90s Nike store was very small percentage of of the total business. But then the store has evolved, right? So for them the, the product performance is the most important. So that's where you want to honed in. If you look at the company like Starbucks, right? So what's up? Obviously coffee, a Starbucks is trying to create a community, but they somehow lost that, lost that direction a little bit, right.

So if, if, if the, the coffee experience and you want to bring people in, then you need to focus on how do you create that local community, How do you create that coffee experience that are unique for you? So it, I think in some ways brands and retailers have to go back to the fundamental, what business are you in and what are you known for? That's where you need to use AI. In the meantime, we talked about this is a marathon with a Sprint.

Yeah, right. You need to have the strategy in who you want to be, but then you also need to have Sprint investment to get you to to your endpoint. So I'd be so. Sorry, go on. I hope you'd answer your question. I know. Does the research then go in go into, for example, a workforce transition in upskilling them

for AI skills? Did you get any data on what that looks like in terms of then the number of organisations that are looking at upskilling or how they get the workforce ready for AI or AI related AI related skills? So IBV, we have specific workforce study that that actually get into the how do you do that? In my study, I wanted to find out where the responsibility, who's training, meaning who's driving the training. Because for me, I'm more on the business side, growing up in

retail. For me, business has to has to determine the agenda because if if the application that I'm using day-to-day have AI, yes, you're going to have new way to learn, you have a new way of doing things. But ultimately I'm the one, right, Because the study also talked about most of the activities going to be augmented. That means the people in the role will be augmented by AI. So it's, it's a little bit tricky. It's not like automation where things going to be automated for you.

You're going to have to decide, you know, let's say generative AI. The most valuable capability of generative AI is to augment knowledge is to summarise information for you. So I think the business need to drive, but then HR has to manage the culture change, right, because it's a change in process. And then it actually have have to have a say in it because it

is ultimately a technology tool. You think about AI governance AI, you know, AI data is, is. So that's why in my study, in this study that I've, I've LED, we, we look at who's responsible. And very interestingly, there is AAI centre of excellence, AI centre of competency. And, and that's pretty high rated.

So the interpreting when we interpreted the data of that is OK. So organisation are thinking about they need to have an AI centre that monitor all the training, but then ITHR and line of business will almost have an even number of seats at the table. So from my study, it looks like where they are in this journey is still pretty early. People have a concept of doing

that. People have identified who's going to be organising it, who's going to be providing the content, who's going to be actually executing it, but it's not set in stone yet, meaning people are still trying to figure out. Yeah, I think that your research said that 87% of executives had some form of AI governance framework that fewer than 25% fully had implemented them. Yes. And is that why is that? Because it's a good thing to do, but really difficult to to?

It's a good thing to say that you're doing, but really difficult to implement? What? What? Why is the discrepancy? Yes, so great question. Again, Alex, you asked a lot of great questions. You're very kind. So we look at AI governance together with the barrier to progress. So we ask question about, you know, so where are you with an AI journey?

Where do you see as the biggest obstacle to progress, to really scale and to really transform AI and privacy, explainability, transparency, all these are on top of mind of business leader. And then we connect that insight with, OK, so are you thinking about it to find that many people are thinking about it, They have actually done work to define the roles and responsibility to, to establish governance, but they are still a little bit lagging in getting the tool, but they are following

the same steps, right? So first you need to assess what you have, then you need to be be clear about, you know, how do you establish roles and responsibility along come the governance right now is to actually doing it. So how we look at the data and interpreted the data is that a lot in a very high percentage, 8090% are doing something, they're thinking about it, they're establishing it, but now they are now have to move into the doing phase, right.

So if you think about or for IBM, there is a Watson governance. So you need a framework, a platform to help you monitor, to help you purge bias and to help you assess your risk on an ongoing basis. This is this is the the challenge that pretty much everybody again, Alex, I'm telling you, this is the first time I see the data moving together so closely with each

other. And and we cover we cover all the continents. We have the UK, we have the US, we have Japan, we have China, we have Southeast Asia with Australia, we have Germany, we have, you know, Switzerland. So very interesting norm we're seeing here. Yeah, I, I. Mean my, my, my take away from that is the, the, the fact that the, the skills needed are embedded in, let's say 3 or 4 areas, supply chain, consumer marketing, you know, data and analysts.

And that's probably why I think people can't go off the beats and track because there's not that many off the beaten track type data outcomes that you can get. And plus how many data silos exist within businesses and how unstructured data, you know, there's so many different areas that you need good quality data to be able to get that AI outcome that doesn't exist. And so therefore, probably you have data or all retailers have data, yes, have data in HR.

And that's, I can see why the real, the real leaders out there will be thinking in that way. How do I get this new data? What do I do to drive that? Three quick questions to sort of close off with as you've been, as you, this is your baby, this is your research. When you are presenting this to executives, what do you find? Where do they go to with this research? What's been the common theme from the people receiving what you're telling them?

Is there like one thing that people keep coming back to and asking you about? Yes, so. People wants details was it was just those right? I was just. It depends on the area. So I presented the study to a group of, of marketers, you know, more of the front end of the house. And what they really want is they're not surprised at the data, but they want to understand what's behind the marketing and customer experience. They want to know because the study that I, you know, I LED,

we have data. So for every area we have 5 key, 5 or 6 key activities. So people want the data and it's great because then I can give them the follow up because it's impossible to cram everything in there. Absolutely right. So I get so number one, I get a lot of head knots. So that's always good. People raise their eyebrows to see the magnitude, not just their area, but all areas. The second thing they asked for is do you have the underlying data for this aggregated data?

So there's a lot of follow up from there. And then the third is really, how do they interpret this data? How do they share it with their team, right? Because many times when I meet, I meet with the, the business leader. So a lot of time they say, well, you know, how do I, how, where do I start?

Question with, you know, you asked initially is there's there's so much so where, where, where do I start and that's where the action guys becomes important and I often use it as a way to close is you have to start somewhere. For example, within IBM we have, but we have our own tool. So I say make it fun. Make it fun for your employees.

We have competition. You want innovation, you drive innovation with people that are currently working in the job. If you know that their job is going to be augmented, in what way can this tool really help them do their job to give you better results as a as a product designer? People are talented. They want to design product that's of good quality. You know, that's what they be measured, right? But instead what happened is people are going through Excel spreadsheet, right?

I used to be a merchandiser, I used to be a planner. You know what, open to buy monthly, month, weekly, Monday meeting really take up a lot of my time because I'm working with Excel spreadsheets. If you're in supply chain, right, oftentimes planners are frustrated because everybody's in the reactive mode because you can't be proactive because there's just not enough time between the close of the week to the morning you show up and you have Monday review meeting.

So I say start somewhere and start with your employee to get ideas in how to drive innovation to better serve the area that you serve. So chances are you have very good employee, they're very good at what they do, but they're

being bogged down right now. I mean, to be fair, that sounds like a, a lovely place to, to sort of end because that's like the, the nugget of wisdom that you would give to the executives receiving the, the thing my, my own curiosity in terms of data points, because you're probably a, you love data. What I think I mean, it could be the, the, the data points I've already mentioned in terms of 52% projected increase in AI spend or 82% planned increase in AIG and integrated business

models. What's the one data? The one data outnumber that you like in your report? What's the one that you keep going back to? I love your. Question, I would say that for me, I as excited to see AI as an enabler to drive growth instead of cutting costs, Save, yeah. Got you. Yeah, Yeah. So so. Yeah, right. So, you know, if you read the report, there are some stats about because we, we ask because I've been doing this for a few years.

So we do have longitudinal analysis and we last question every year for a five year horizon. So where do you see AI contribute as a driver to save costs? And then how do you see AI contribute to revenue growth? And I was really, really excited this year to see when we asked last year was where do they say they see AI as a contribution to revenue growth.

And we asked them 20 last year, this year and the next year, right, Yeah. And what I see is the percentage of AI contribution to revenue growth is going to crossover. It's going to crossover, meaning it's going to go higher in the next in the next three years. So I know we have to save costs definitely, you know, otherwise, you know, where's the margin going to come from? But do understand that AI is a tool that help you improve productivity gain right now.

Once you're ready to scale, it has the opportunity to drive revenue growth. That's the one thing that get me really excited is, is like, other than looking at productivity gain, saving cost, be more efficient. This is a transformational tool that can help you try growth. That's and is there is. There one question that you people are missing when they look at the data. Is there like something that you think you you, you were expecting people to ask you about, but they don't ask you

about? Just again, from having done this before, are there things that people are fundamentally missing in their approach to AII guess? I think that's the last question that you asked me. That's the question that people don't don't really ask people. I think, I think people are in an interesting place right now because 2024 is the year where people experiment, right. A lot of whether you are in it, HR, customer service, everybody, whether you're a store, everybody is experimenting it.

And then this year is how do you scale it? When you look at scaling, you need investment, Yeah, right. You need dollar investment. And we see the investment in it. You know, people are dedicated in it, but people want to know where's the return? Yeah, yeah. And I think, I think I mean, I when I work in retail also very, very, very often we think about technology tool to help with efficiency. That's where we see the margin

game, right? So you look at price, you look at, but I think AI has has the opportunity to, to turn the table around. Think about, don't think about how do you do markdown better think about how do you get your product right, so you can sell it at full price because because people are willing to pay for it, whether it's because the quality is there, whether because it's more convenient for them, whether it's because it aligned with their value.

You know, if if you if you know their brand purpose, right, whether it's to support the purpose. I think AI has the opportunity for brands and retailer to rethink how how do they get because how and to build customer loyalty. Yeah, you know what I mean.

So I I. Think I think they're the rabbit holes they, they can depending on who within the business is looking at it. So if it's marketing or product in the sense of personalization, am I personalising on, you know, discount and and whatever am I personalising to maximise the recommended retail price that we're putting out there?

Right. Well, and I don't know, there's a lot of, you know, I've heard people say people are just giving discounts where they don't need to be discounting, they're marking down where they don't need to be marking down. But I guess data has been always lacking to do that effectively, right? So. So a retailer that I love and I'm a loyal customer. I mean because, because I used to live in the Pacific Northwest. Is REI OK?

If I think about REI as as a retailer, if you can provide them services, if you, if you can leverage data to extend your services. Let's say I got into biking, I got into cycling, but I'm useless in putting a bike together. It's actually more complicated than I thought and actually needed help.

So if I purchased a bike like a fat tyre bike, then you know, a purse a person may not have to in may not have enough time, like the store associates may not have enough time to look at my profile to see I'm a beginner and I live in the Pacific Northwest and I would love to have the opportunity to engage in activities with my local community, right? If you have all this in your, you know, the store associates

all that at the fingertip. Not only can they help me with my bike, they can offer me how to enrich my experience. There's a better chance that I would just keep going back for my gear because, you know, I need a helmet, I need hands, you know what I mean? In a way you sort of expand the experience, your product experience because your store associate or the customer service person who's helping you have all this information available.

By the way, just to just to end with like a number that personal. I responds with follow up action in customer service. The investment of AI is going to double this year because everybody you know is have virtual assistant, they have a chat box and help you. But now 2025 is the year where they think about how do you personalise it, not just for promotion, right, Personalise and follow up action. So think beyond pricing, think

about services. That's one of the the high stat, which is 89% of executive are expecting AI to innovate product and services. And this is just one simple example. You have all the data, you have my purchasing history, you know where I live. But it's a matter of connecting data to create insight, to make it matters, to make an impact. Yeah. I think that's a wonderful. I mean, obviously I can keep going. I've got 100 questions I can ask

you. But Jane, thank you so much for sharing those insights with us. I'm really grateful. Thank you for. Having me and have a great day. Thank you.