CommerceAI

Ian Jindal (00:01.717)
Hello, dear listener, and welcome back to the Commerce AI podcast studio, where we're picking up on the conversations we're having with leaders in the direct-to-consumer space, looking at the commercial impact of AI on their roles, their companies, the customer, and more broadly, the world in general. I'm Ian Jindal, the founder of RetailX, and it's a great pleasure to have with me in the studio today, David Rose.

who is the VP of International Technology at Papa John's. David, welcome to the studio.

David (00:37.89)
Thank you very much, Ian. Thanks for having me.

Ian Jindal (00:39.957)
Good. So three important things in there. There was who you are, your role and Papa John's. So let's get everyone up to speed with each of those in any order you fancy.

David (00:52.142)
Not at all. Yeah, well thank you. As you mentioned, I'm the VP of International Technology at Papa John's. Papa John's is what we call works in the quick service retail sector, so we make and serve and deliver delicious pizzas to people around the world. we have just over six thousand stores around the world, with the majority of those in the US, where we originated in Kentucky. So that's three and a half thousand stores in the US.

And then we have another sort of two and a half in international markets as well, around 50 markets around the world. So UK is our probably largest international market at about 400, 450 stores. and then we have a really nice diverse section of markets, several hundred stores like China, South Korea, Peru, Chile, Spain. it's a fantastic portfolio of markets. really interesting, obviously, huge local.

Ian Jindal (01:44.832)
Wow.

David (01:50.496)
and differing appetites for pizza within those markets, which which always makes it really great.

Ian Jindal (01:53.823)
And is there a sort of consistent pizza or is it very highly localized with nothing other than the bread base in common? mean, is this the lingua franca of culinary palates?

David (02:06.848)
It it is, and there's definitely if you think, you know, pizza and its origins is a wonderful dough base with a maybe a tomato base and cheese. it can be as simple as that. obviously as Papa John's we have a few staples. you know, cheese and tomato and pepperoni are the two sort of favourites that that occupy the majority of our sales, but we also make sure we have a lot of innovation. and that can be centrally done.

some of the global innovation we've done recently include a croissant pizza where we've used croissant pastry to deliver a delightful flaky buttery crust. but we can also in go hungry on that. That's maybe a little more of a premium side. but also in the UK, for example, we've just launched a sourdough range. So we we are very well known for fresh unfrozen dough. That's the kind of magic ingredient that we

Ian Jindal (02:39.295)
my god.

Ian Jindal (02:43.039)
Right. Everybody has just instantly gone hungry, just like that.

David (03:01.432)
have consistently the same everywhere across the world. and then of course, both for local palates but also local supply chains, sometimes our ingredients and and taste preferences can be different around the region. I visited our China market a couple of years ago and I think the special then was pineapple deep fried prawns and a pepperoni mix on a pizza. so that that was

Ian Jindal (03:24.713)
I'm up for that. Just bring me that combo.

David (03:28.536)
That was a great combo. and some markets like China have amazing innovation. Consumers expect almost a new pizza every month. and it might not take a a large percentage of sales, but it's a fantastic way of keeping the brand top of mind and and testing out different partnerships.

Ian Jindal (03:45.601)
So, I mean, we're going to come back in a second to your role in a technology sense, but let's maybe explore a little this balance between consistency and innovation. So if you're in the digital domain, then you can innovate at the speed of light, change a few pixels, have a laugh, move on. Whereas it's very difficult to innovate with food safety and quality.

David (03:50.99)
Mm-hmm.

Ian Jindal (04:14.465)
and also with physical items across the globe. So you've got this situation where you can't mess around with classics. You have to have consistency country by country, week by week, restaurant by restaurant. But yet you've also mentioned innovation at a couple of times. So when you get up in the morning, aren't you conflicted between, I must hold on to this perfect model of optimized efficiency?

but I also do innovate. So how do those two parts of the brain work together at this sort of scale and with these sort of responsibilities?

David (04:53.964)
Yeah, I think certainly and starting with the consistency piece, that's that's the bedrock of of how we work and certainly at our scale. so you know, when people think about ordering a pizza, they'd like a tasty pizza turning up quickly and largely it needs to be hot and ready to eat as soon as it's arrived. and doing that across six thousand stores, doing that every single day, sometimes into late early mornings, is a big operational task. And that's why

Big brands like ours, we really operate at scale and all of our processes and a lot of our innovation is focused around keeping ahead and on to that task. so we we largely don't see ourselves as a top-down brand. We're actually we call ourselves our headquarters is actually a restaurant support center because the essence of our business is in every single store.

where people are putting together the ingredients through the ovens and getting it out the door on the onto you know and relying on a driver network as well to deliver those pizzas. So we are doing all our work to support that simple operation. Simple, but operating at scale is is not so simple in in that extent. So consistency, both of product, both of delivery and operations is is is really core to it.

Ian Jindal (06:02.955)
Yes.

David (06:11.81)
But I think then when we're looking at how do we you you basically you will survive as a business if you deliver that. But to succeed as a business and to grow as a business, innovation is then required. Not just obviously to stand out against competitors, but to keep customers interested and as you adopt to customers change changing trends. So you mentioned, of course, there's product innovation. and typically

as well as working in pizza, I've I've also worked in the coffee world as well. We typically have a sort of twelve to eighteen month innovation cycle where our our fantastic food RD teams will be looking at customer trends from across the whole culinary world and starting to tease out what might be relevant for us. And then they go through product development, product testing, supply chain sourcing, et cetera, et cetera, all the way to the end of a launch of a product. Now alongside you've got product innovation, of course, as you mentioned, we're

I do like to think of us as almost as an e-commerce brand. About 80% of our revenue comes through first or third party digital channels. So our experience is as much as around getting that hot pizza, great tasting pizza to people's homes, as much as actually the experience of ordering the pizza as well. So there's innovation in the channels that we deliver, but also in the channels that people can order through. And then there's some innovation into how we actually get pizzas to them.

Ian Jindal (07:25.235)
Yes.

David (07:35.432)
typically the model has been we have drivers in store who deliver the pizzas. Of course, increasingly so, almost to the majority now we rely on third party drivers. but we're also, I think you if you look on the news, we've experimented with using drones to deliver in in America in a a small part of of the geography where it works. So there's lots of innovation thinking around the whole operation, as much as the experience that customers can have as well.

Ian Jindal (08:02.569)
Right, now I think that's a good intersection for us to swap on to the changing world, but I want to be a little bit disciplined to myself because I think our listener will benefit from getting a thumbnail career sketch of what you've been up to, because you touched there on your coffee background, but looking over your LinkedIn career,

as I encourage our listener to go and immediately stalk you, the links in the notes. You've covered a lot of sectors. So before we go on to the changes in the, know, quick restaurant sector, just talk us through how you ended up at Papa John and the industry you've been, because I ticked off, you know, NHS and various other things. So it's quite a broad set of

very complicated scaled problems which have now brought you to pizza. So just draw that line for us and what you've taken from each of those career moves.

David (09:01.71)
Mm-hmm.

David (09:10.818)
Yeah, sure. So yeah, l as we said at the start, today today I'm in technology at Papa John's. but I've actually new to technology, albeit I've had some digital product past. My long term history has largely been in the marketing space, sales, marketing, loyalty, that sort of world. so I started my career, I actually started my career way early in the with the British Army and the and the charity world, which gave me a great foundation for independent leadership and some

I guess early experience of the world through my travels with those jobs. Then I pivoted more my first kick kick off my business career was in aviation. so I spent two years ten years at Virgin Atlantic covering a wide variety of of global roles and commercial roles. and that really continued my taste and interest into global consumer trend. So at at heart I'm a B2C

Marketeer, that doesn't necessarily mean I just campaign. I like to think of customer experience and how we're creating products and experiences for customers. So actually, you know, when I think about aviation, 10 years there, I then transitioned to to coffee to worked for Starbucks in their AMEA region, as one does, following a a previous manager. Then I transitioned during the pandemic to the NHS and actually specifically into blood donation at the NHS.

Ian Jindal (10:23.903)
As one does.

David (10:36.286)
which again is a B to C product. We're trying to sell appointments to people to come to a retail environment and give blood and to come back time and time again in in a in the form of loyalty and retention, right?

Ian Jindal (10:48.929)
I've never thought it quite as loyalty to attention, but I'll give you that one.

David (10:53.112)
But but exactly the very similar business model. And then since then I've actually returned back to the quick service retail space, largely because I I find fast food is fast, it's fast trends, it's fast moving, innovation needs to be done quickly. and the pace of change is is fantastically interesting. And and returning to a global role as well really helps me keep my finger on the pulse of

geopolitical events, consumer trends around the world, it's always a very interesting space in that site.

Ian Jindal (11:22.879)
Okay, so I'm going to maybe sketch a line here, which you may reject, of course. But looking at it, what struck me was that you seemed to operate as this layer between super quick changing and fickle customers and very difficult to change, but pretending to be agile infrastructure.

So it doesn't matter how clever you are, you can't change the NHS blood donation in a couple of months. So you could try and move the edifice while also talking agile. So it seems to me as if you've found this, you know, maybe it's a friction layer or a lubrication layer between the unreasonable rapid demands of the customer with difficult, large engineering things.

David (11:57.87)
Mm-hmm.

Ian Jindal (12:20.299)
that you can't just mess around with. you're a bit like, I don't know, the gristle, the cartilage between the bones, the sort of slidey layer in between, which if you accept that in any way does make the current work on AI quite interesting because you've got yet another frothy accelerant in the market that is moving faster than the underlying currents.

David (12:39.82)
Yes.

Ian Jindal (12:49.259)
can move in the business. He says mangling that metaphor instantly.

David (12:53.12)
No, I think I think that's no, I I think that's a great articulation of of me, maybe I guess. I'd I'd say if one was to allow to say that my superpower is being able to influence change at scale. and I think being working both in aviation, but in particular I do enjoy working with challenger brands like Virgin Atlantic, Papa John's. we're not the largest in the world, we're still a very large enterprise.

Ian Jindal (13:07.967)
Nice. Yeah.

David (13:22.306)
But being a challenger brand allows it gives you a little more license to take a few risks, move a little more quickly, because you're smaller, you're little more agile, and typically customers give you the license to be a little more innovative and risk taking in that sense. so to your point and and perhaps drawing a little bridge, my current role is not only covering international technology, but I also oversee and I guess program director for Papa John's AI efforts.

Ian Jindal (13:38.322)
interesting.

David (13:50.998)
a across our business. yeah.

Ian Jindal (13:52.619)
Again, sorry, I don't want be rude here. you know, our listener might be thinking, come on Ian, give the guy a break. But you've gone from marketing to IT to AI and the smile hasn't left your face. So, of course, as a well-trained professional, we all like to take on challenges and learn new skills, et cetera, et cetera. But it is quite a jump for someone to say,

David (14:05.102)
Mm-hmm.

Ian Jindal (14:20.865)
David, what a great marketing career you've had. The IT chair is a bit empty. Could you look after that? How did that actually come about where someone thought this marketing guy can take on IT as well?

David (14:34.818)
So I that's fair. I'd I'd say the bridge has been two pieces. One is digital product. I'd say I'm a product guy at heart, and that's I'd I actually always say any marketing person is always actually thinking about the customer experience. Either they're selling it, they're designing it, they're creating it. So I think at heart I'd say most product people are marketers and most marketers are are product people. but today's products are largely

digital online in that respect, to certainly in B2C environments in the companies I've worked with. So I would qualify myself of less as of a techie and a computer scientist in that sense. but with my commercial background and my customer-facing background, I bring that customer lead role to the technology department or the technology asks. Now one of the advantages of operating international technology is a lot of

Ian Jindal (15:27.509)
Good.

David (15:31.678)
Mar our local markets do the hard work of actually building the tech, working with vendors in that side. we provide a governance role in overseeing the brand experience that comes to a result as a result of it. So it's a very sort of product-heavy in that side. Now, that said, I think two, three years ago, I was when I was transitioning out of the NHS back into the private sector, that was when ChatGPT launched. We were starting to dabble using it both in the NHS.

writing papers, it was all just content generation at that stage. and I realized for my longer term future career, I'd like to think I've got another 20 years in the this is going to have a huge impact. and the breadth of sector experience and with my commercial head on, actually I felt it was very suited to my background and experience to to go head first into the the sector. So I've done two two things really

One is I during a period of unemployment between before I joined Papa John's, I invested myself in a in a sort of one of those executive AI courses at at Oxford Side Business School. That was the kind of launch pad to getting a real grasp of the foundations of the tech sector. And then since then I I've been quite disciplined of always updating my learning once a year, but also experimenting and practicing with AI in my private life as well as well as my work.

So I have been probably a little more disciplined in this in this discipline than I have in the past in deliberately pivoting into the subject and thinking very carefully about how I apply it to work, how I apply it to the business. and that's clearly been successful in terms of it's now l led me to be able to lead a tech team, but also I I do like to say, you know, in

Ian Jindal (17:13.237)
Fascinating.

David (17:22.222)
in there's not many experts who have ever done no one's done this before, right? I have no mentor to learn from. There is no boss who who's done this before. So what excites me and keeps me intellectually interested is anything that anyone's learning today has never been learned before in AI. So everyone has the opportunity to be at the front line, to be cutting edge in its literal sense.

And that's a fantastic place to be if you're if you're looking to change your career or advance your career or or or if you're driven like me and just learning these these new and exciting things.

Ian Jindal (17:59.893)
Yeah, I mean, I think that's just so well put and interesting. Last year, I put all of the past podcast episodes, know, decades worth of interviews, and I asked the AI to draw out any common points. So, you know, cross sector, cross gender, cross age, background, etc, etc. And the two characteristics of the AI said

ran through all of the interviews was the propensity of people for continuous learning and a characteristic openness about sharing what they've learned. And so, you know, maybe that should be the topic of the podcast going forward. Now, let's get practical again, because you have this learning, you bring it to Papa John, it's a fast moving sector at a fast moving time. That's fun.

David (18:36.558)
Hey, Chelsea.

David (18:41.624)
Mm-hmm.

Ian Jindal (18:57.771)
But you also said a few heartbeats ago about the governance role. We've already talked about the quality assurance is baked in. So let's look organizationally, whether within Papa John or elsewhere in this bright, shiny world where we could all become next page gurus or learning. There's no set path. How do you manage an organization that's full of excitement and daring do?

but yet has a propensity to break things that cannot and must not ever be broken. So how do you balance this pace of innovation, risk taking, being the challenger, but also not screwing up big time?

David (19:44.746)
It's a it that's the classic question. That is the question I think a lot of enterprises are asking. And as well as looking back, I guess, on the last two years on how we've done it and found our way to doing it well. And I'd say that's that's been an exploration. because like I said, nobody's done this before. but also it's been interesting talking with a few people externally around where businesses are taking slightly different models to how we did it.

So there's a little bit of saying, I don't think there's a right or a wrong wrong way. what I would encourage is that everyone try and articulate what the way is for them. And there are people with you know FOMO fear of missing out. There's a lot of people worried about competitor risk. There's lot of people in businesses who are worried about their whole business will collapse. I'd say for me, a lot of that worry comes from just not having an approach. And actually

By doing some of the courses like I've done, talking to others, there are some common consistent pieces that if you put in place, you might not they might not bring the answers immediately, but but they'll bring a framework for you to find the answers. And that can often help calm the worry. So for example, like I often think and revisit this ourselves, but we've landed on, I guess, on three core pieces that I'd recommend as probably safe for any business to put in place.

The first of all, to you to your point is put some governance around this. Now some businesses have great governance, especially like coming from healthcare. You've got a lot of governance in a in a life critical space. So some people might have governance already in place that can be adopted for AI implementation, but often those that governance can be very slow moving, hugely restrictive, and therefore you actually risk slowing down the pace of innovation.

Ian Jindal (21:23.772)
Yes.

David (21:39.958)
we rebuilt our governance from scratch, for for AI innovation in particular, largely because AI technology was something we'd obviously we'd never done before. but the pace of change was so quickly we felt it needed a new process. So we've set up a really simple governance process. It's four stage gates. It's like, you know, set up an intake form, approve the pilot, do an evaluate the pilot, and then approve it for production.

So I I liken it of sticking this process on the nose of our usual process. So it's like a pre-innovation process that allows people to move quickly, comfortably, but make sure all those who are involved in checking on risks are involved so that they don't get unduly worried by people just going off and creating chaos. so the governance process is one place. The second piece is is a structured program of innovation.

And that's, I think, taking a good hard look at what your strategy is and just where your innovation should be focused. I I think in the early days, a lot of companies, and us included, just went for the fun stuff. Ooh, AI can do this, let's try it. And actually we started getting pulled off strategy, doing pilots that weren't relevant to the general success of the business. so a lot of those pilots failed or just didn't get very far.

But also a lot of executives started to get frustrated because they were like, why am I best talent going off and doing something that's not relevant? So I'd recommend keep your innovation delivering strategy. And then the third piece, the last piece, I think, which is definitely a passion point for me, is considering more generally AI literacy as an objective and and a and a goal. and this asks for things like how are you training your staff, building an AI academy.

How are you thinking both broad as how everyone is using these this new software, but also deep around particular roles that might need radical reshaping or radical changes to their work, be it computer engineers who are writing the next website or marketeers who are no longer writing content in that sense? So those three things are j largely, I think, are probably true in most businesses, and how we how I thought of applying

David (23:56.448)
AI transformation at scale across our business.

Ian Jindal (23:57.835)
Yeah. So again, there's a risk of a of a looped argument there, which is if you take your first stage, you're at the project acceptance and so on, then if you don't have people who are AI literate, they won't see the risks because they'll be judging it against a risk matrix for Excel spreadsheets rather than, you know, autonomous agents, for example.

David (24:19.937)
Mm-hmm. Yeah.

Ian Jindal (24:27.455)
And then also as people go through the process and learn, how does that learning get disseminated? So two practical questions there. One is keeping the gatekeepers knowing what to gatekeep. And then secondly, how do you develop that beyond just those pioneers who've done one or two good projects, but then maybe some fizzle out or goes where, how do you bring that back into the business?

David (24:40.396)
Mm-hmm. Yeah.

David (24:53.154)
Yeah, I think that's I think that's a th those three areas are going to evolve. and so to be candid, we we started very light and as soon as I joined my boss then, I was a director then, I got license to go and try a few things. so this was two years ago, so it was a very different environment AI environment then. actually we went and tried a lot of pilots and to be candid, I probably created more problems than I solved.

and so when our Kevin, our CTO, joined, he came to me and said, I need you to put out all your fires and build something a little more, build some governance that controls this a little better. so I sort of I guess I turned a gentle conversation. I I turned poacher to GameKeeper. So having built the governance, and of course consulted with all my colleagues in infosecture infosecurity, legal, risk, etc.

Ian Jindal (25:36.267)
That's a very gentle conversation to be had.

David (25:52.432)
we created this AI committee, oversight committee, who all needed to have sight on what we were doing, so that both it was done safely, but also they were confident we were doing it with a long term sort of health in mind. and that immediately putting that process in place just immediately gave everyone a little more confidence. There was something the process was being run well. it does need to be run well, and and actually you could argue I am the gatekeeper as much as the champion.

but that's a lovely tension in my role where I'm very sensitive. If I if if I let something through that shouldn't have been let through, you lose trust overall in the governance process. but we've learned, like I said, so our first few pilots, we put a little bit of funding, we had no internal capacity to build AI agents. so we brought in a couple of vendors to help us. I'd say, you know, we had a 50-50 success rate on some of those early agents.

but it was interesting to both see the opportunity from the pilots we built as well as actually see how the vendor worked themselves. So a mix, a mix. So we again take quite a structured approach to the pilots themselves. I won't go into too much detail, but we're very considered around customer facing is one opportunity, internal changing the way we run our business is the way I like to call it, is another opportunity. And then personal tools is perhaps a third.

Ian Jindal (26:55.851)
Sorry, were these customer facing agents or were these internal? Right.

David (27:20.28)
So we picked a variety of initial pilots that tested all three of those areas, both generative technology, agentic technology, text, video. So the first pilots were really about testing the tech as much as testing our capability of implementing the tech. And that's where we made some early learnings. Now we did that with vendors to support, but now we've actually building our own internal applied AI team.

So it's very much an evolution in process where we do it for six months, we see what's working well, what needs to change, and then we adapt. So the governance process itself has been tweaked, the program has been tweaked, our strategy's changed, obviously, in the last two years as a business reacting to you know what's what's facing the world. so sometimes our pilots have to be pushed a little bit of a different direction in that sense.

Ian Jindal (28:11.393)
So let's look at the people side of this, because you mentioned now you have your own sort of native AI teams in the business. Where have they come from? Because we've sort of admitted that in a way you are a neophyte to the AI world. You took your previous learning, you did that structured learning, and

you you've developed professionally, but the people you're recruiting are maybe early in their careers or specialists. So where is this new group of people coming from? Are you seeing them transitioning from being product people, merchandisers, food scientists, marketers converting within the business? Or are you hiring new skill sets from outside or development parts? Just tell me what it looks like two years into a program.

David (29:06.456)
Sure, sure.

Ian Jindal (29:08.949)
versus that, hey, we're all new at this stage.

David (29:12.034)
Yes, yeah. So I I think actually first of all, I look internally, because there are already teams that have been using AI for a long time. Data science data teams that are very and were in the last two years, certainly initially, they were the source for a lot of this early innovation. you know, they've been applying machine learning techniques for many decades to some of their statistical work. you'll get even some, you know, areas in marketing, certainly in CRM, where

some of that technology's been applied for quite a long time as well. So you'll find a lot of people, it's already their role. Certainly, AI is in the broader scheme. Generative AI is is new. but those individuals who've been working with machine learning AI generally have the good practices, they know what an AI pipeline is, they know how to develop, test, and implement some of this types of technology. so there's some really great foundations you can.

Ian Jindal (29:51.136)
Yes.

David (30:10.998)
tap into there. Secondly, I'd say you in any company that has great talent, I'd say some of the one of the biggest things is you probably found from your insights over the la last few years of podcasts, great talent is largely good at self-development. And what I found by openly inquiring and just going and talking to teams, you will find people who are on the side already learning and investigating AI.

Because they're interested in it. They want to self-learn. And actually, one of the toughest tasks I've had is surfacing that passion in a business. because often people are a little bit reticent of being the AI guy or girl or coming forward with ideas, or perhaps acting a little bit out of policy or worried that they might be out of policy. So often the opportunity is to to brand something. We have something called PJX, which is our kind of internal AI team. It's it's not a team, it's just a

collection of people who who want to put up their hands and say, hey, I'm interested in this. So we provide an environment for people to come and speak to me, raise their hands, come with ideas, a safe space, if you will, in terms of that innovation. And then the third piece is you you might have to go externally. And so initially we well, we have our partnership with Google Cloud, which we signed up a couple of years ago. They've both brought fantastic

knowledgeable AI practitioners into our business to work with us. We've just launched in the last month our voice AI voice ordering product in America that they've built with us. But they also recommend some fantastic vendors who are on the Google Partnership program. And so we've worked with two or three of them in the last year who have helped get us started. And often once they've done a few work, we look at it and go, actually this isn't too difficult. This is

There's some very traditional software work here that we can get our internal teams to do. And then we might hire contractors or recruit full time in that respect. in yeah. So I think now we're definitely more confident to recruit permanently, given we're we know we're a little more confident in the direction and the skills that we need.

Ian Jindal (32:08.256)
Yeah.

Ian Jindal (32:14.485)
Hmm. So.

Ian Jindal (32:24.193)
So confidence was the word that I was going to sort of hold up to you, just listening to what you said, this ability to listen to the team, to surface those skills, but also to learn from contractors and then pick things up yourselves. I mean, that's a very idyllic sounding way of working. If we maybe just skip a generational two and look...

to the junior intakes within your organisation. We've been covering a lot in other analysis pieces about youth unemployment, the skills that people need upon entering the workspace and so on. And yet you've also given us a picture of people whose skills are being continually honed, developed and used elsewhere. So if we take these two sides, being

What type of person in terms of skills and attitude do you think is needed in the new Papa John's staff entry pool as a result of AI? And as you think or ponder that, I'm just also going to track back and think every 10 years we have a quote unquote technology revolution.

that supposedly changes everything, but yet somehow doesn't as well. So we had the other databases in the 80s, work for the 90s, web in the noughties, maybe let's say APIs and mobile in the teens. and look, we're at AI. And as you said, the actual AI has been here for 20 years, just not generative, not speaking back to us. So as we look at this, maybe fifth decadent roll of the dice,

David (33:54.136)
Mm-hmm.

David (34:06.35)
Mm-hmm.

Ian Jindal (34:19.659)
where we're saying the world has changed, do you think it's changed in terms of the skills and people you want coming in at a junior level, and if so, how?

David (34:30.198)
Well it's a tough question. it it's a tough question in two parts because I think firstly, I don't think this is like another a previous change. I think the others have largely been still around the bedrock of standard computer science. It's just been we've seen opportunities in scale of data or scale of business can move to the cloud or onto the web. It's largely been reacting to where customers would love us to go around.

and bringing more convenience in that side. So I think there's something just around intelligence or or the mimic of intelligence that we're getting from this technology that I don't think we have the answers yet and how that's going to impact. but also I think secondly there is without a doubt taking my business and individual hat off, there's there's a social worry here I think which is very valid.

across all the businesses that I've worked in, there are many roles which work on which do manual repetitive tasks. and people are very happy working those tasks. They go home, they do their nine to five, they have a fulfilling life outside of work. the this AI technology, automation's always been there, right? We've always been able to automate things.

However, AI does make it a lot easier because it just allows automation, and certainly the software that's been built around AI allows automation to be implemented much quicker and remove the difficulties of it in the past. Now, in two senses, I'm I'm worried that a material part of our sector will see disruption, and I don't think we're ready for that. I don't think socially we're ready for that, politically we're ready for that. I don't think those conversations are yet happening. They're starting to, which is great.

So I have a worry in that sense, but I'm also quite optimistic in another sense that we do control how this is implemented. and that's why my passion point is looking towards AI literacy and building AI academies, because I think if as businesses, and I think we are much more socially aware as businesses now, our impact on the community, what to your point around new entrants to the workplace, or people who have been in the workplace forty, fifty years.

David (36:51.852)
I think we're much more sensitive to that. Our investors, our boards expect that much more from us. So I'm hopeful that many, many more businesses will start to appreciate their role in preparing both their current workforce, but also helping give the signals to the new workforce on what the future of work is going to be like. so I'm there's a little bit of a dichotomy, right? I'm a little bit worried, but I think worry fear is not good. Worry is good. Worry

Ian Jindal (37:11.413)
Wonderful.

David (37:19.446)
encourages planning, encourages thinking. and that's what I I like to sort of look to the worry, not the fear, in that sense.

Ian Jindal (37:27.773)
I think if ever anyone says what's the benefit of an early military training, I think that's probably the answer there. you know, worry not fear. Well, David, that's fantastic. I think you have answered the question that no one had, which is why on June the 3rd is David talking about the AI powered organization? So, dear listener.

David (37:35.192)
Yeah.

Ian Jindal (37:54.301)
If you look at your digital calendar and you see that this date is before the 3rd of June, you have a chance to come and meet David at the Commerce AI event. If, however, this is after the 3rd of June, I can only say it's a little sliver of what you've missed, but just as well we've recorded this. So, David, thank you for joining us on the podcast and giving us that insight.

into both change and think a level of consistency around learning development, knowing what needs to be done. And thank you as well for being a participant in the upcoming Commerce AI event. But for now, it's a goodbye from the studio with a final thank you to David and we'll see you in the next episode. David, thank you so much.

David (38:44.654)
Thank you very much. Thank you.