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AI in Retail: How Executives Are Embedding AI · The Retail Podcast

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  I think AI is going to be a capability, it's going to be an
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  enabler that is going to be embedded in everything you do.
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  Hello and welcome to the Retail Podcast.
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  We are now into the post NRF retail podcast guests that I
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  couldn't get together with at NRF just due to the sheer volume
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  for for for the guests as well as myself.
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  Jane Chung is one of such guests the from the IBM Institute.
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  Sorry, the I'll start. Well, actually we could keep it
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  from IBM, the institute business value part of our game, which is
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  ultimately the thought leadership and the research and
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  they had some research they had a quick look at I think it came
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  out it was just before or during NRF.
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  But rather than me butcher all of the details about the
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  research, Jane, what give us an give us a view of what you do
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  within IBM or the IBV and then what is the research that we're
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  going to be talking about? Sure.
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  Thank you. Thank you, Alex.
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  It's a pleasure to be here. You know, like you said, it's
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  post NRF, although it feels like long ago, but it's only a couple
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  weeks ago. So thank you for inviting me to
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  have a chat about the research. My role within the Institute of
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  Business Value, which is part of IBM, is to work with the key
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  stakeholder within IBM to determine the research agenda
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  every year. So every other year we work on a
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  global consumer research study and then every and then the
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  other every other year we work on executive research study.
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  So I launched the latest IBB consumer research study a few
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  days before NRF, so on January 8th.
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  And no surprise is, is about AI, but it's, it's a research based
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  on five that based on 5000 executive who, who are
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  responsible of AI initiative. So we do have a screening
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  process for people who participate.
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  We want to make sure that the executive, the leaders of our
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  participants, not only are they knowledgeable, but they actually
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  are responsible of AI initiative.
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  This year's study is very broad. We talked to we interviewed
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  executive across 13 different area, Alex.
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  So is from the front end of the house, which is customer
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  experience stores to product design, product development,
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  merchandising, inventory management to supply chain
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  operation and then also the corporate function like HR,
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  finance and IT. So very rich study.
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  One of the challenge is so much data, but to actually drive
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  insight that really matters. So that's, that's what, that's
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  what the study is is about. I'm already fascinated.
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  First question, It's not one that I send you.
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  What's the one? Yeah, let's go.
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  What's the one? Because I, I, I mean, what's the
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  one thing that surprised you? Because you've got a fantastic
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  pool of people to, to, to have data and you've got data coming
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  from every angle. What, what was the one thing
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  that you thought, oh wow, what's the oh wow piece of data?
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  It's. So I've I worked in retail for
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  30 years. So between in the industry as a
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  consultant and now with the doing research.
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  What surprised me the most with this study is how uniform and
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  we're talking about data and I love data, how uniform the data
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  are across all area. So for example, you know, I
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  started working in retail in the 90s.
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  I remember Y2K. So there is the E com wave,
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  right? So it's the E com and then E com
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  is really about the front, the selling of it, of the, of the
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  products, right? And then there's the mobile
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  commerce, social commerce. So then the anchor is always
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  around selling the product, not that the back end is not
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  important, not that operation is not important.
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  And then you know, COVID hit the world and then also by supply
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  chain disruption. So then the supply chain
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  inventory become really, really critical and everybody become
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  more, you have to be digital, right?
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  And I think that just shifted everybody's behaviour.
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  So then it's OK. How do you engage with consumer
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  and how do you get the product? This always seems like a
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  dominant area where we need to focus on this year.
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  I keep going back to look at the data.
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  Initially it's like, am I seeing the right number, big number
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  across all areas. So, you know, if you look at the
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  report, we're talking about organisation that are expanding
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  the use of AI and across 14 area almost the same unison like
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  right, right. So very big number between 80 to
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  90%. That means everybody is
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  expanding the use of AI. And then it's like, OK, what do
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  you oh, you know, where's the focus, where's the trend?
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  So that was the big surprise initially when I just look at
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  the number, well, when I think about it, does that make sense?
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  Yeah. So that's quite interesting then
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  is that mean? So it has it moved away from AI,
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  evolve it's evolving role in retail as a tool or because
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  obviously first you do some experimentation, then you look
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  at your business process and you know, how do I optimise the
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  business process and put AI as part of that optimization.
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  So what do you, what's the research showing?
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  Are people actually integrating AI?
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  What is the evolving role of AI? That's a very good question,
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  Alex. So if you think about it, if
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  just look at it and that helps us like at the end, we took a
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  step back and, and we, we decided on the title, which is
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  embedding AI in your brand's DNAAI is going to be embedded in
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  everything you do. It's almost like, it's almost
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  like the Internet without even knowing it, you will be using
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  AI. The reason why I said that is
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  because not only our company consciously making investments.
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  So if you look at the budget, we talk about the budget, right?
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  AI as a budget as a best part of the IT budget as part of the
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  technology tool. What we're seeing is the growth
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  of AI spend actually is higher in the line of business.
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  So, so then I talked to a lot of our leaders who are working with
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  our client. We have partners like Microsoft
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  is a partner of ours, Adobe is a partner of ours and our
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  partners, all these solution are have AI embedded in it.
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  So whether you know it or not, you're going to be using AI,
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  right? So, so AI is going to be
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  embedded in everything we do, just like everyone knows how to
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  Google. If you want to find something,
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  it's going to be Google. But here now is you will be able
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  to get richer in like a Gemini, right?
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  Like you will be able to get richer information.
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  It's almost like it has expanded your search capability and it
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  has offered your capability using ChatGPT.
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  Students are using it, right, in summarising knowledge, in
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  augmenting knowledge. So I think AI is going to be a
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  capability. It's going to be an enabler that
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  is going to be embedded in everything you do.
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  Yeah, I, I want 100% agree with that.
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  And, and in the sense that most of the SAS providers have now
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  got an AI bot as the interface at once or they've got one or
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  they're building 1 or there's one in, in beta that basically
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  you don't go to the to the software anymore, You go to the
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  agent. And I think even ChatGPT has
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  released an agent. What's it called?
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  Automation, I can't remember. It was only released a couple of
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  days ago that basically it goes off as an agent and helps you in
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  the real world, I don't know, buy flowers and, and stuff like
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  that. So I, I can definitely see that
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  when you look at your research for retailers and in what areas,
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  because everyone, you know, I think the, the statistics are
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  52% projected increase in spending AI.
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  What are those applications retailers are thinking about?
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  I think this links to the first question that you said that
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  surprised you that they're all the same.
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  What? But what parts of the business
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  are they? Yeah, so that's a very good
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  question because after I got I, I was preparing to talk to you.
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  I actually went to look at the details and it's very uniform.
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  What I mean by that is, you know, on and on average, when
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  you look at the aggregate of average, you look at the AI
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  spend outside of IT was 52% increase.
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  When I look through the 13 different area, the percentage
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  is within 5%, meaning it's about 45% in some area, like in some
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  area is a little bit over 52%. So the the deviation of this is
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  is very close. So it's it's a little bit hard
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  to say which area is is going to be more important in in a in AI
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  application. Very.
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  Yeah. So you didn't get that because
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  again, you were saying, you know, whether it goes into
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  supply chain or marketing or customer experience, you don't
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  have a sense of which one will get the lion's share of
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  investment from your research. No, no.
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  And, and one of the one of you know, you think about the data
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  and one of we always provide an, an action guide, right?
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  So one of the important, important action guy that
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  retailers, brands and retailers, vertical retailers too, they
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  need to decide what is the most important priority because
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  obviously AI is a capability that can do everything.
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  Yeah. So what's your core, what's
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  what's the most important for you?
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  And you also need to balance the investment versus return of
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  investment, right. So you really need to, I think
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  it's highly adaptable, it's a good way.
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  But then you also need to think about the way can it give you
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  the most in ROI? And then what's your brand DNA?
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  So for example, I used to work for Nike and Nike is all about
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  performance. So any product that they
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  produce, it has to enhance the athlete performance.
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  So if you know that, then guess what product is very important.
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  Even though they even though they have stores, right?
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  They have flagship. So when I work at 90, Nike in
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  the 90s Nike store was very small percentage of of the total
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  business. But then the store has evolved,
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  right? So for them the, the product
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  performance is the most important.
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  So that's where you want to honed in.
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  If you look at the company like Starbucks, right?
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  So what's up? Obviously coffee, a Starbucks is
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  trying to create a community, but they somehow lost that, lost
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  that direction a little bit, right.
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  So if, if, if the, the coffee experience and you want to bring
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  people in, then you need to focus on how do you create that
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  local community, How do you create that coffee experience
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  that are unique for you? So it, I think in some ways
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  brands and retailers have to go back to the fundamental, what
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  business are you in and what are you known for?
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  That's where you need to use AI. In the meantime, we talked about
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  this is a marathon with a Sprint.
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  Yeah, right. You need to have the strategy in
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  who you want to be, but then you also need to have Sprint
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  investment to get you to to your endpoint.
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  So I'd be so. Sorry, go on.
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  I hope you'd answer your question.
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  I know. Does the research then go in go
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  into, for example, a workforce transition in upskilling them
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  for AI skills? Did you get any data on what
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  that looks like in terms of then the number of organisations that
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  are looking at upskilling or how they get the workforce ready for
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  AI or AI related AI related skills?
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  So IBV, we have specific workforce study that that
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  actually get into the how do you do that?
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  In my study, I wanted to find out where the responsibility,
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  who's training, meaning who's driving the training.
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  Because for me, I'm more on the business side, growing up in
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  retail. For me, business has to has to
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  determine the agenda because if if the application that I'm
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  using day-to-day have AI, yes, you're going to have new way to
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  learn, you have a new way of doing things.
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  But ultimately I'm the one, right, Because the study also
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  talked about most of the activities going to be
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  augmented. That means the people in the
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  role will be augmented by AI. So it's, it's a little bit
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  tricky. It's not like automation where
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  things going to be automated for you.
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  You're going to have to decide, you know, let's say generative
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  AI. The most valuable capability of
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  generative AI is to augment knowledge is to summarise
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  information for you. So I think the business need to
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  drive, but then HR has to manage the culture change, right,
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  because it's a change in process.
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  And then it actually have have to have a say in it because it
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  is ultimately a technology tool. You think about AI governance
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  AI, you know, AI data is, is. So that's why in my study, in
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  this study that I've, I've LED, we, we look at who's
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  responsible. And very interestingly, there is
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  AAI centre of excellence, AI centre of competency.
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  And, and that's pretty high rated.
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  So the interpreting when we interpreted the data of that is
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  OK. So organisation are thinking
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  about they need to have an AI centre that monitor all the
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  training, but then ITHR and line of business will almost have an
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  even number of seats at the table.
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  So from my study, it looks like where they are in this journey
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  is still pretty early. People have a concept of doing
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  that. People have identified who's
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  going to be organising it, who's going to be providing the
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  content, who's going to be actually executing it, but it's
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  not set in stone yet, meaning people are still trying to
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  figure out. Yeah, I think that your research
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  said that 87% of executives had some form of AI governance
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  framework that fewer than 25% fully had implemented them.
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  Yes. And is that why is that?
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  Because it's a good thing to do, but really difficult to to?
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  It's a good thing to say that you're doing, but really
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  difficult to implement? What?
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  What? Why is the discrepancy?
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  Yes, so great question. Again, Alex, you asked a lot of
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  great questions. You're very kind.
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  So we look at AI governance together with the barrier to
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  progress. So we ask question about, you
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  know, so where are you with an AI journey?
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  Where do you see as the biggest obstacle to progress, to really
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  scale and to really transform AI and privacy, explainability,
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  transparency, all these are on top of mind of business leader.
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  And then we connect that insight with, OK, so are you thinking
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  about it to find that many people are thinking about it,
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  They have actually done work to define the roles and
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  responsibility to, to establish governance, but they are still a
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  little bit lagging in getting the tool, but they are following
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  the same steps, right? So first you need to assess what
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  you have, then you need to be be clear about, you know, how do
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  you establish roles and responsibility along come the
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  governance right now is to actually doing it.
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  So how we look at the data and interpreted the data is that a
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  lot in a very high percentage, 8090% are doing something,
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  they're thinking about it, they're establishing it, but now
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  they are now have to move into the doing phase, right.
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  So if you think about or for IBM, there is a Watson
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  governance. So you need a framework, a
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  platform to help you monitor, to help you purge bias and to help
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  you assess your risk on an ongoing basis.
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  This is this is the the challenge that pretty much
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  everybody again, Alex, I'm telling you, this is the first
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  time I see the data moving together so closely with each
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  other. And and we cover we cover all
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  the continents. We have the UK, we have the US,
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  we have Japan, we have China, we have Southeast Asia with
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  Australia, we have Germany, we have, you know, Switzerland.
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  So very interesting norm we're seeing here.
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  Yeah, I, I. Mean my, my, my take away from
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  that is the, the, the fact that the, the skills needed are
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  embedded in, let's say 3 or 4 areas, supply chain, consumer
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  marketing, you know, data and analysts.
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  And that's probably why I think people can't go off the beats
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  and track because there's not that many off the beaten track
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  type data outcomes that you can get.
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  And plus how many data silos exist within businesses and how
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  unstructured data, you know, there's so many different areas
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  that you need good quality data to be able to get that AI
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  outcome that doesn't exist. And so therefore, probably you
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  have data or all retailers have data, yes, have data in HR.
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  And that's, I can see why the real, the real leaders out there
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  will be thinking in that way. How do I get this new data?
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  What do I do to drive that? Three quick questions to sort of
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  close off with as you've been, as you, this is your baby, this
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  is your research. When you are presenting this to
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  executives, what do you find? Where do they go to with this
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  research? What's been the common theme
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  from the people receiving what you're telling them?
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  Is there like one thing that people keep coming back to and
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  asking you about? Yes, so.
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  People wants details was it was just those right?
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  I was just. It depends on the area.
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  So I presented the study to a group of, of marketers, you
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  know, more of the front end of the house.
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  And what they really want is they're not surprised at the
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  data, but they want to understand what's behind the
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  marketing and customer experience.
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  They want to know because the study that I, you know, I LED,
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  we have data. So for every area we have 5 key,
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  5 or 6 key activities. So people want the data and it's
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  great because then I can give them the follow up because it's
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  impossible to cram everything in there.
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  Absolutely right. So I get so number one, I get a
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  lot of head knots. So that's always good.
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  People raise their eyebrows to see the magnitude, not just
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  their area, but all areas. The second thing they asked for
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  is do you have the underlying data for this aggregated data?
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  So there's a lot of follow up from there.
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  And then the third is really, how do they interpret this data?
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  How do they share it with their team, right?
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  Because many times when I meet, I meet with the, the business
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  leader. So a lot of time they say, well,
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  you know, how do I, how, where do I start?
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  Question with, you know, you asked initially is there's
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  there's so much so where, where, where do I start and that's
• 20:14
  where the action guys becomes important and I often use it as
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  a way to close is you have to start somewhere.
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  For example, within IBM we have, but we have our own tool.
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  So I say make it fun. Make it fun for your employees.
• 20:30
  We have competition. You want innovation, you drive
• 20:33
  innovation with people that are currently working in the job.
• 20:36
  If you know that their job is going to be augmented, in what
• 20:39
  way can this tool really help them do their job to give you
• 20:44
  better results as a as a product designer?
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  People are talented. They want to design product
• 20:49
  that's of good quality. You know, that's what they be
• 20:51
  measured, right? But instead what happened is
• 20:53
  people are going through Excel spreadsheet, right?
• 20:56
  I used to be a merchandiser, I used to be a planner.
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  You know what, open to buy monthly, month, weekly, Monday
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  meeting really take up a lot of my time because I'm working with
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  Excel spreadsheets. If you're in supply chain,
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  right, oftentimes planners are frustrated because everybody's
• 21:12
  in the reactive mode because you can't be proactive because
• 21:15
  there's just not enough time between the close of the week to
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  the morning you show up and you have Monday review meeting.
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  So I say start somewhere and start with your employee to get
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  ideas in how to drive innovation to better serve the area that
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  you serve. So chances are you have very
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  good employee, they're very good at what they do, but they're
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  being bogged down right now. I mean, to be fair, that sounds
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  like a, a lovely place to, to sort of end because that's like
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  the, the nugget of wisdom that you would give to the executives
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  receiving the, the thing my, my own curiosity in terms of data
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  points, because you're probably a, you love data.
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  What I think I mean, it could be the, the, the data points I've
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  already mentioned in terms of 52% projected increase in AI
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  spend or 82% planned increase in AIG and integrated business
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  models. What's the one data?
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  The one data outnumber that you like in your report?
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  What's the one that you keep going back to?
• 22:12
  I love your. Question, I would say that for
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  me, I as excited to see AI as an enabler to drive growth instead
• 22:22
  of cutting costs, Save, yeah. Got you.
• 22:24
  Yeah, Yeah. So so.
• 22:27
  Yeah, right. So, you know, if you read the
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  report, there are some stats about because we, we ask because
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  I've been doing this for a few years.
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  So we do have longitudinal analysis and we last question
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  every year for a five year horizon.
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  So where do you see AI contribute as a driver to save
• 22:46
  costs? And then how do you see AI
• 22:48
  contribute to revenue growth? And I was really, really excited
• 22:53
  this year to see when we asked last year was where do they say
• 22:57
  they see AI as a contribution to revenue growth.
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  And we asked them 20 last year, this year and the next year,
• 23:04
  right, Yeah. And what I see is the percentage
• 23:08
  of AI contribution to revenue growth is going to crossover.
• 23:13
  It's going to crossover, meaning it's going to go higher in the
• 23:17
  next in the next three years. So I know we have to save costs
• 23:21
  definitely, you know, otherwise, you know, where's the margin
• 23:24
  going to come from? But do understand that AI is a
• 23:27
  tool that help you improve productivity gain right now.
• 23:30
  Once you're ready to scale, it has the opportunity to drive
• 23:35
  revenue growth. That's the one thing that get me
• 23:38
  really excited is, is like, other than looking at
• 23:42
  productivity gain, saving cost, be more efficient.
• 23:46
  This is a transformational tool that can help you try growth.
• 23:50
  That's and is there is. There one question that you
• 23:53
  people are missing when they look at the data.
• 23:55
  Is there like something that you think you you, you were
• 23:58
  expecting people to ask you about, but they don't ask you
• 24:00
  about? Just again, from having done
• 24:03
  this before, are there things that people are fundamentally
• 24:06
  missing in their approach to AII guess?
• 24:09
  I think that's the last question that you asked me.
• 24:12
  That's the question that people don't don't really ask people.
• 24:15
  I think, I think people are in an interesting place right now
• 24:18
  because 2024 is the year where people experiment, right.
• 24:22
  A lot of whether you are in it, HR, customer service, everybody,
• 24:27
  whether you're a store, everybody is experimenting it.
• 24:30
  And then this year is how do you scale it?
• 24:33
  When you look at scaling, you need investment, Yeah, right.
• 24:36
  You need dollar investment. And we see the investment in it.
• 24:40
  You know, people are dedicated in it, but people want to know
• 24:42
  where's the return? Yeah, yeah.
• 24:44
  And I think, I think I mean, I when I work in retail also very,
• 24:49
  very, very often we think about technology tool to help with
• 24:54
  efficiency. That's where we see the margin
• 24:57
  game, right? So you look at price, you look
• 24:58
  at, but I think AI has has the opportunity to, to turn the
• 25:03
  table around. Think about, don't think about
• 25:06
  how do you do markdown better think about how do you get your
• 25:11
  product right, so you can sell it at full price because because
• 25:15
  people are willing to pay for it, whether it's because the
• 25:19
  quality is there, whether because it's more convenient for
• 25:23
  them, whether it's because it aligned with their value.
• 25:26
  You know, if if you if you know their brand purpose, right,
• 25:30
  whether it's to support the purpose.
• 25:32
  I think AI has the opportunity for brands and retailer to
• 25:37
  rethink how how do they get because how and to build
• 25:41
  customer loyalty. Yeah, you know what I mean.
• 25:45
  So I I. Think I think they're the rabbit
• 25:47
  holes they, they can depending on who within the business is
• 25:51
  looking at it. So if it's marketing or product
• 25:56
  in the sense of personalization, am I personalising on, you know,
• 26:01
  discount and and whatever am I personalising to maximise the
• 26:06
  recommended retail price that we're putting out there?
• 26:08
  Right. Well, and I don't know, there's
• 26:10
  a lot of, you know, I've heard people say people are just
• 26:14
  giving discounts where they don't need to be discounting,
• 26:17
  they're marking down where they don't need to be marking down.
• 26:20
  But I guess data has been always lacking to do that effectively,
• 26:24
  right? So.
• 26:25
  So a retailer that I love and I'm a loyal customer.
• 26:28
  I mean because, because I used to live in the Pacific
• 26:31
  Northwest. Is REI OK?
• 26:33
  If I think about REI as as a retailer, if you can provide
• 26:37
  them services, if you, if you can leverage data to extend your
• 26:43
  services. Let's say I got into biking, I
• 26:46
  got into cycling, but I'm useless in putting a bike
• 26:49
  together. It's actually more complicated
• 26:52
  than I thought and actually needed help.
• 26:55
  So if I purchased a bike like a fat tyre bike, then you know, a
• 27:01
  purse a person may not have to in may not have enough time,
• 27:05
  like the store associates may not have enough time to look at
• 27:08
  my profile to see I'm a beginner and I live in the Pacific
• 27:11
  Northwest and I would love to have the opportunity to engage
• 27:16
  in activities with my local community, right?
• 27:18
  If you have all this in your, you know, the store associates
• 27:22
  all that at the fingertip. Not only can they help me with
• 27:26
  my bike, they can offer me how to enrich my experience.
• 27:31
  There's a better chance that I would just keep going back for
• 27:34
  my gear because, you know, I need a helmet, I need hands, you
• 27:37
  know what I mean? In a way you sort of expand the
• 27:42
  experience, your product experience because your store
• 27:47
  associate or the customer service person who's helping you
• 27:50
  have all this information available.
• 27:53
  By the way, just to just to end with like a number that
• 27:57
  personal. I responds with follow up action
• 28:00
  in customer service. The investment of AI is going to
• 28:04
  double this year because everybody you know is have
• 28:10
  virtual assistant, they have a chat box and help you.
• 28:12
  But now 2025 is the year where they think about how do you
• 28:16
  personalise it, not just for promotion, right, Personalise
• 28:20
  and follow up action. So think beyond pricing, think
• 28:26
  about services. That's one of the the high stat,
• 28:29
  which is 89% of executive are expecting AI to innovate product
• 28:35
  and services. And this is just one simple
• 28:38
  example. You have all the data, you have
• 28:40
  my purchasing history, you know where I live.
• 28:42
  But it's a matter of connecting data to create insight, to make
• 28:48
  it matters, to make an impact. Yeah.
• 28:51
  I think that's a wonderful. I mean, obviously I can keep
• 28:53
  going. I've got 100 questions I can ask
• 28:55
  you. But Jane, thank you so much for
• 28:57
  sharing those insights with us. I'm really grateful.
• 29:00
  Thank you for. Having me and have a great day.
• 29:02
  Thank you.