Cloud Reset – The Podcast | Episode 8: The AI Decisions Boards Expect CIOs to Get Right by 2030 with Peter James
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Episode Summary:
Episode Summary:
In this episode of Cloud Reset, Jono and Naran catch up with Peter James—Chairman of Macquarie Technology Group, MYOB, and DroneShield—to talk about the AI decisions CIOs need to nail today to stay ahead by 2030. Peter’s been deep in the tech game for decades, and he gives a straight-up Board-level take on what really matters when it comes to AI, leadership, and staying competitive.
Here’s what you’ll get from this episode:
- Why waiting for a perfect AI plan is a waste of time—start experimenting now
- How to find and back the “mad scientists” in your team who can drive real change
- Why owning and understanding your data is non-negotiable
- What Boards are actually expecting from CIOs when it comes to AI adoption
- How AI will flatten hierarchies and shake up traditional leadership models
Peter also drops one of our favourite lines: Don’t chase where AI is today—go where the puck is going. If you’re a tech leader who wants to make the right calls now and stay ahead of the curve, you’ll want to tune in.
Episode Transcript:
All right. Welcome back to cloud reset episode two of our AI series, where we cast ourselves forward five years, we become time travelers and we figure out now that we’re adopting AI and our business is high performing and we’re serving our customers better than ever. How did we get there?
Got it. So everything’s successful. Everything lived up to the hype. It’s all worked exactly as we wanted it to. Our business is running leaner. Our operations are smooth and slick and agile. We’re more competitive in market. Our customers are happier. It’s all worked as we expected it to. What decisions do we make together?
Yeah, exactly. How did we get there?
What can we do right now to set us on the right path? And we are excited because we’re going to be talking to some of our industry’s heavy hitters about this topic.
We are indeed. Now. In terms of what we’ve been up to lately, it’s fair to say that, um, I would say the requests upon us are businesses that are well and truly on that journey.
Um, one of the things I loved about Steven’s conversation, so Steven Worrall from a few weeks ago, um, was this concept of lived experience, in that you should form an opinion on AI based on, Real world experience. Get your hands dirty, roll up your sleeves. Surely there’s somebody within your organisation with some aspiration and ideally some free cycles that can play with this technology and you can then have an informed position.
Exactly. And I really love that. And if you look at what we’ve been up to, even since then for the last couple of weeks and a little bit before that, but we’re really doubling down on this, looking for the mad scientists. That’s right. How do you go and find the mad scientists in your organisation? With the ideas and nurture that proof of concept that be agile, run pilots and see what you can get out of it.
It’s super interesting. And I know now, and you’ve been involved in a few projects of late.
Yeah, no, true. So look within our own business, it really starts with a problem. It starts with something that. We feel can lend itself to the technology. So if we think about our security business, it was a case of streamlining the triage process and how can we get more efficient with our ability to respond to incidents in a timely manner.
That was one good example. Another one was Having the information to hand to make decisions about our customers and our interactions in real time and interfacing with the technologies that we’re all in front of every day. So things like Teams, for example, it could be driving into work. I want to know, before I meet a customer on a Monday morning, how are we tracking on Net Promoter Score?
Uh, what products have they purchased? Are there opportunities for them to explore other products with us? Uh, and more importantly, are they happy with what we’re doing? Things of that nature. I want to draw upon all of those key insights before I go into that meeting such that I can be well informed and the conversation is going to be productive the second I sit down.
Yeah, that one’s a super interesting one. Another one that I’ve actually really been enjoying is looking at how we respond to RFPs.
Right.
Especially in the cybersecurity space where you’re looking at a lot of GRC type, uh, questions and responses. There’s a lot of repetitive information there, a lot of heavy lifting.
How do we take some of the heavy lifting out of that and look at all of the responses that we’ve done before and empower our people to just do more and be faster and be more accurate. So that’s actually a really interesting one that is starting to pay off as well.
Now I know that across those examples, and this goes back to that lived experience piece.
There was no way for us to properly scope those projects the way they turned out. And what I mean by that is the resulting solution for us is vastly different to how we could have possibly imagined it to turn out. Uh, the iteration, uh, one of the solutions, for example, has got 20 different models in play.
That wasn’t on anyone’s schematic. It wasn’t in any design. It wasn’t a foresight of anyone to suggest that that’s how that solution was going to play out. And yet that’s where we landed. And it was only through iteration and POC and, Luckily enough, having the people within our business with the aspiration and the capability and the free cycles to be able to iterate and test those solutions to produce that outcome.
But I know that it’s changed our opinions and I know that future projects around generative AI will be informed by everything that we learnt from those projects and I think that’s really what Steven was getting at. I think through rolling up your sleeves and, and having the luxury, admittedly, right, to play with these things means that we have an informed position.
And when we scope another project, um, we’re just that further down the road in order to make the decisions necessary for that project to be successful.
I think that’s right. And it’s that iteration that’s going to take the industry forward.
Yep. That’s it.
Well, we’re really looking forward to this episode.
Can’t wait to introduce our guests. Let’s get into it.
Okie doke. Well, it’s with great pleasure now that I’m going to introduce our guest. Our guest is a gentleman by the name of Peter James. I’ve known Peter for at least the six and a half years that I’ve been working for Macquarie Technology Group. Peter has a career that spans many decades. He’s a programmer at heart.
That’s where he started. It’s very useful in the conversation we’ll be having around AI, but more recently, Peter is the chairman of Macquarie Technology Group. He’s also the chairman of MYOB, and he’s on the board of directors for DroneShield as well. Peter, welcome to the Cloud
Reset podcast. Welcome Peter.
Thank you, Naran. Thank you, Jono. Yes, a programmer. I often say that, uh, I was a programmer back in the days when, uh, people were called programmers, not developers, and I actually programmed in languages that have been long forgotten, or people have never heard of. But it’s, uh, something that stood me in good stead throughout my career.
Long career in the tech industry, but it’s great to be here.
Thank you. Welcome, Peter. All right. Now the key question, and this is in line with our AI series. What are some of the critical decisions that you see Australian businesses making now, today, to be successful with generative AI five years from today?
And the short answer. You’re not going to like this. I don’t know. Oh, goodness me. I don’t know, so we can stop the conversation there. But perhaps I might expand on that. If you Google white papers and AI, you’ll get dozens, hundreds of documents coming at you. And there’s so many experts in AI. There’s everyone, every consultant, every tech company is putting out their views on AI.
And the short answer is, We just don’t know. But when I sit around the boards, uh, and, uh, we’re looking at, uh, just exactly what do we do, people are asking the question. How do we differentiate? How do we separate the wheat from the chaff? How do we actually make decisions that are going to future proof us going forward?
And I often say the best predictor of the future is look back at the past. And we look through all of the great developments in technology. And the beautiful thing about technology is it never stops moving, never stops developing. If you look at, uh, the whole question of the internet. and interactivity.
If you look at mobility, if you look at cloud and virtualisation, each of these were massive changes and developments. And you know what? AI is no different. And we talk about AI as being new. AI is not new. The term was first coined, heaven help us, back in the fifties by a computer scientist by the name of John McCarthy.
So I’d suggest we’re, we’re still at the beginning and in five years time, we will still be at the beginning. But what I can say in a company, you need the right culture. You need a culture of innovation, of iteration. You have to be inquisitive. And you also, you can read all the white papers. You can, Sit there and analyze and hear what people have to say.
But the best thing often is just get started. Uh, and, and one of the great companies that I’ve been involved in Ansarada, uh, with Sam Riley, uh, got, and it’s a tech company. He got cross, uh, functional teams together. And, uh, we, we actually had hackathons and we looked at how can we. Uh, learn about AI, not from the desk, not from papers, but how can we actually learn from, uh, developers, from looking at productivity, looking at external and looking at perhaps new models.
So, have the right culture. Be prepared to innovate, be prepared to iterate, invest a little, perhaps not too much to start with, learn, not from the papers, but learn by doing.
Jono, this is awfully consistent with what um, Steven Worrall, who was on the podcast a couple of weeks ago said, having an informed position, lived experience, There’s so much on YouTube, there’s so much in the news, there’s so much that we read about this stuff.
Um, play around with it.
Yeah, play around it, get your hands dirty. And, and also, as I said, in five years time we’ll still be at the beginning. And, and like all of the other changes that we’ve had. In the internet, virtualisation, et cetera. Um, there will be changes to the way we work, live and play, but this one’s more profound.
It’s, it will touch and is touching every part of the way that we live, the way we work, and as I said, the way that we play. And the best way is just get started, get your hands dirty. And the other thing, uh, it’s not just about the CTO, about the CISO. This is right across the business. Every, every part of every business and every business.
Yeah. Naran and I were talking about that earlier and. Especially after the last podcast that we did with Steven Worrall talking about that idea of, you know, nurturing the mad scientist, right? Who’s got, who’s got the idea that we can invest in and, you know, proof of concept trial, make small iterative investments.
And learn something, you know, and those ideas come from crazy places all over the business, all different, all different roles have a, in the business have a part to play in, uh, adopting this technology.
We’ve all got to be a little bit crazy. We’ve all got to get outside our comfort zone because the business models that we have today, many of them are going to change so profoundly.
And one of the things I’ve learned. Is when you have an established business and you’re trying to change it, you know, that analogy of flying the plane and changing the engine at the same time, it is a very difficult thing to do. And the whole concept of innovation from within and having those mad scientists, having someone or a group who are able to perhaps just, uh, roam a bit free and try new things.
Uh, and, and I’m sure we get on it. the topic today. But Australia, we don’t like failure either. You know, we’ve got to have, um, the ability to get out and try new things and be prepared to fail a bit.
It feels like a luxury to me, Jono, the fact that, um, within our business, Um, we have a number of naturally inspired, motivated people who we can afford the free cycles and the time to play and to proof of concept.
That feels like a luxury to me, Peter. I’m wondering, you know, are we just in a fortunate position in our business? Do other businesses have that same luxury, and if not, how can they create that?
Yeah, look, it’s, it’s, um, it’s a really good question. And having been in business all my career, and yes, I started as a programmer, but reasonably quickly morphed into business.
Often businesses And they are so tight in terms of cost or revenue, but certainly, uh, talking about Macquarie technology, we do have the ability. We’ve got 200 certified engineers. And might I also say that, um, Any, any business, you shouldn’t try and do it all yourself, you should have a partner. And whether it’s Macquarie Technology or someone else, don’t try and do it all yourself.
One of my, um, pet hates is the Not Invented Here Syndrome, and I’ve probably been guilty of it myself. You know, we’re special, we’re going to do it all ourselves, we don’t need outside help. Well, in AI, you do, uh, not too many, but, uh, do a lot yourself, but have a partner who can afford to invest in new technologies, can afford to have people try new things, and can afford to travel the world and look at the trends and bring them back and support you in your journey.
Yeah, we talk a lot about that, that balance sheet for innovation, you know, how do you access that? And if you don’t have it yourself, it’s, you need to lean on a partner.
And, and that’s true and, and I, I was talking earlier about one of the great Aussie tech companies that I’ve had the privilege to work with, iiNet, and we used to look at, um, in the early days when we were small, we were nimble and we were able to make decisions over a weekend.
A new pricing plan would come out and we’d have one. You know, from a competitor, we have one in the market two days later, as we got bigger and bigger and bigger and multi billion dollar company, it became harder to innovate and having a partner who can sit outside and help you innovate and be more nimble is a good thing.
Look, and I’m encouraged by that. Um, so, you know, John, I were talking about what have we been up to in the last couple of weeks. And, um, there’s a very large financial services organisation that’s called us in and they want to do a multi level, I wouldn’t say indoctrination, but it’s a lived experience conversation with the board, with the exec teams.
And then they want to, I think do like the hackathon. staff workshops with the various engineers in their business, because they’ve decided that they want their own informed decision. We’re grateful that they’ve invited us in to help them with that as well. Um, and they want to land exactly where we wanted to be as a business, you know, I don’t know how long ago it was, now when we started playing with this stuff, a couple of years.
Um, they want to form their own opinion. Uh, and they’ve decided that now is the time. They’re bringing us in to take advice from us on what worked, what didn’t, how do we iterate. And I tell you, the pace of innovation, I know that just one of our projects, the models changed in real time. Like, one week the team were working in one direction, the next week there’s a new model, new LLAMA iteration, for example, and they’re using that.
And that was happening, like, almost on a daily basis. The pace of innovation is incredible and I think going back to the original question of, you know, what decisions do you have to make now to be successful in five years? I think the light is on and I think organisations are now making those decisions.
And, and the point you make is, is one of speed. And, uh, you know, we’ve talked about the history of technology, but this almost has a mind of its own. And, uh, it’s, it’s not just happening in North America, it’s happening all around the world and I’m sure we’ll get on to China at some stage. You know, we tend to live in our own, perhaps, uh, Western bubble, uh, but right around the world, um, technologies are moving.
And then when we’re surprised, when all of a sudden something new pops up, we shouldn’t be surprised it’s going to be like this. And, you know, I suspect we’ll talk about leadership models because leadership models are going to change. You know, people are going to have to be fast moving, quick to respond.
And one of my passionate, um, perspectives in technology is where the puck is going, that ice hockey, um, Canadian, uh, Uh, expert, uh, ice hockey player, Wayne Gretzky, uh, he always said, where the puck is going, don’t go where technology is today. Try and work out where it’s going to be. I wouldn’t say in 12 months time, perhaps in 12 days time.
Yeah.
We, we talked about this on the last episode, um, around other nations looking to this technology to leapfrog in terms of their economic development and, you know, rising up in the pecking order. Sort of geopolitically, and we saw, uh, DeepSeek. Hit the market. That was, seemed to be a surprise for everybody.
It sort of shook everybody up. I know, Naran, you’ve been, you’ve gone pretty deep on this. No, I have. I think deep is the word, right? So
I think we’re remiss not to talk about DeepSeek and just the, um, the disruption. in the AI landscape that DeepSeek has created and proves what it demonstrates to us that it’s not all about having billions of dollars in the deepest pockets that innovation can come from anywhere.
I wonder whether, um, a lack of resources, um, created an excess of innovation in this instance, right? And worked in the opposite direction. I’d love to get your thoughts on that. Yeah, look,
it’s, it’s fascinating. All of a sudden the world’s surprised. Why, why should we be surprised? That, um, China, of all nations, has come out with some world leading technology.
And, you know, we talk about, um, things happening quickly. You know, they’ve been working on this for an amount of time. And the market, the stock market in the U. S. was surprised. I mean, NVIDIA’s stock dropped 600 billion in one day. That’s a trillion Aussie dollars. The biggest fall, 17 percent of their market cap in one day.
The biggest fall on the U. S. stock market ever. But if you looked at the stock, and that was in late, late January. If you look at the stock price last night for NVIDIA, guess what? It’s back pretty much to where it was. So, um, We’re going to have these shocks, but as I said, they shouldn’t be shocks. And quite a few years ago, I actually went to visit Huawei in China.
And I was so impressed with the number of PhDs that they’ve got working on projects. The Chinese are very good fast followers. Why should it surprise us that they’re going to come out with perhaps a lower cost model. Now, the good thing is, um, you know, there’s some downsides to that and we can talk about sovereignty and security and, you know, China and, and data.
But this means that AI is likely to be democratised and rather than it just be the purvey, the, the place where the big companies, the big tech companies are doing great work. But this means that You know, apps AI is more likely, not necessarily through China, but it does show that AI can be democratised.
And, and that means that, you know, more and more companies, more and more people will be able to get their hands on this. And of course, that means more data explosion. We go to data centers and there’s a lot of places we could take that conversation.
Yeah, it’s incredible talking about the pace and democratisation of AI, we talk about, you know, Australia being, we think the tech industry, you know, where we’re early adopters, we get told that the Australian market are early adopters.
We hear that a lot. Um, but I wonder, Peter, what’s your view on what could be actually holding Australian business back from adoption? So maybe if we assume for a moment, we could be going faster. What’s holding us back?
Yeah.
Look,
uh, don’t get me started. Um, that was the point. That was the idea. You’re in a safe place.
It’s a safe place. How long have we got, guys? It’s a private conversation. Private conversation. We’re not recording. No. Okay. Um, look, uh, Aussie, uh, we’re great innovators and, and we do. Um, we’re early adopters and we have to be because, you know, the tyranny of distance. But you know, I sometimes wonder that are we going to end up being mediocre, mediocre through the middle?
Why do I say that? I mentioned before, we, we don’t like failure for a start and the tall poppy syndrome is still alive and well in this country. Um, and then we’ve got, um, regulation. Uh, and you know, the regulation side of AI is something that’s fundamentally important about security, about privacy, etc.
And we were just talking about, um, China. But this is an economic arms race. And you mentioned other countries are looking at this to get economic advantage. I mean, we’re fortunate we’ve got all of those, um, Uh, minerals or et cetera in the ground, but we can’t rely on that forever. You know, we are and we have to be a knowledge based country and that’s where AI just becomes more and more important.
You know, at a heart, we can be great innovators and I’ll throw out a, uh, a company that you may know a little about, DroneShield, I’m actually chair of DroneShield and we founded that company back in the early days where the puck is going. We could see that small drones off the shelf, uh, were going to be everywhere, were going to be prolific.
What we could also see was they were going to be used for nefarious, um, bad reasons. So we took a decision eight years ago. That’s where we were going to play. That’s where the puck was going. Well, guess what? It took the Ukraine war to bring us into perspective. So now there’s a company that detects and jams drones.
But we’re actually using AI on the battlefield in Ukraine to detect actually out of all of the, um, the electronic signals. What is a drone? What’s it likely to do? And we’re actually getting, uh, when we jam a drone, We’re getting the software uploaded to the engineers here in Sydney, and they’re, they’re looking at, uh, because for every good thing we do, the other side is making changes to their technology.
So there’s an Aussie company that can move quickly. Yep. But it’s, it’s forced to because of a warfare situation.
So that means this just for the benefit of our audience, I was enjoying all the content on DroneShield online. Just listen to this for a sec. So DroneShield provides counter UAS solutions that focus on radio frequency sensing, artificial intelligence and machine learning, sensor fusion, electronic warfare, rapid prototyping and military spec manufacturing.
Right. So this is, this is an organisation that, that has to innovate in order to be relevant. In, I don’t want to call this a market in, in an environment, um, in a terrestrial situation.
And I think that’s an example of what can be done. We’ll, we’ll come back to, I think where Jono is going is, you know, probably where we tend to be more conservative.
But, you know, if we look at DroneShields, a company that didn’t exist, it’s an industry that didn’t exist seven or eight years ago. And we’ve raised 7 million, got out into the market. And we have, I talked about iterating, we’ve just iterated. Like heck, because of real life situations, and now employ nearly 300 engineers here in Sydney who are doing this, so we can do it, but more and more, I think we, we tend to be conservative, we’re cautious, and we’ve got this yin and yang of regulation.
And, you know, that regulation is fundamental, it’s essential, but it can hold us back, uh, in a world where, you know, we like to think the world’s focused on Sydney, Australia or maybe Australia. It’s not. It could be in, in terms of AI, we’ve seen it’s in China. It’s, it’s no doubt in other parts of the world.
In your, your capacity on the, on the various boards that you’re involved with. It’s balancing act between businesses doubling down on their known good successes and trying to forecast off into the future versus, um, This, uh, the ever evolving landscape and the innovation that’s expected now in market.
How would an organisation balance, um, forecasting based on what’s known to be good and what’s worked fine in the past versus change that’s inevitable and it could be right on the doorstep. How do you juggle that?
Yeah, it’s a tough one. It’s exciting one. It’s a scary one. Um, the first thing, you know, you look at is productivity internal and that’s obvious because every, um, Company, every country, you know, Australia, we talk about being better at productivity, getting better productivity.
That’s the first thing you must do and that’s getting better at what you do today. And that’s the, that’s the puck that’s right in front of your nose. You then look at, you know, I think customer experience is another area where, and we at Macquarie Tech, we built that company. You know, David Tudehope, you guys, we’ve built it based on net promoter score and customer experience, constantly looking, so I’d suggest that’s the next area to play.
But the interesting one, the scary one is, is perhaps a little over the horizon to the new business model, something that we don’t know today. But could well disintermediate us, you know, you can wake up one day and find your business model is gone or is, you know, severely, um, impacted by, by AI and you can’t wait till it gets to you.
And I’ve seen this, you know, many times in industry where, you know, we’ll keep milking. The, the business that we’ve got today, we’ll keep running that hard and that’s where you’ve got to be brave and, and have these, what were we talking them, uh, talking about them, John, are the crazy scientists, the mad scientists, the mad scientists, having people and in a company like Macquarie, we’ve got the ability to have those people, um, Trying new models, trying new things, and then bringing it back in, um, and, and tending to disrupt the existing model.
And that is a whole conversation.
I think that’s super interesting. And it sort of leads me to another question. I love your analogy. I think the Wayne Gretzky analogy of like where the puck is going, where the puck is going in business. I wonder as, uh, this technology continues to develop. The way that we predict where the puck is going is going to change.
And perhaps when we reach. Uh, levels of, for example, general intelligence. Uh, the AI is going to tell us where the puck is going. Yeah, and what happens then?
Yeah, I mean, that’s, that’s a fascinating one. And I mean, the question You know, people get asked is, you know, how long is it before we reach AGI? And I mean, again, my simple answer is, I don’t know.
And every, if you ask 10 people, you’ll get 10 answers from two to three years to two to three decades. I mean, but the reality is it is going to continue to change. And also the definition of AGI will get more and more sophisticated. But we have to recognize that the way we work, live and play is going to constantly change.
And you know, people talk about, is it going to change for the better? I think, you know, by and large it will, you know, I’m a big believer in, in humanity and our ability to take technology to deploy it. Occasionally there’s bad uses of technology, but I’m a big believer in, uh, in us being able to harness that technology by and large for good.
But by heavens, our world is going to change and change fundamentally. It
sure is. And I would say, Look, the internet is wide open with the various definitions of general intelligence. We tried to put Steven Worrall on the spot a few weeks ago. Apparently in the contract between OpenAI and Microsoft, there’s this hidden definition.
Because should OpenAI achieve general intelligence, that’s when the relationship with Microsoft stops. So clearly that’s in their contractual artifacts. So they won’t share that definition. Steven wasn’t aware of it. If he was, he didn’t want to talk to me about it on the podcast. But nonetheless, we asked the question.
Um, I think domain specific, um, general intelligence is happening all over the place. This concept of general, this lovely little definition that I dragged out of some Azure documentation. This is Microsoft being particularly creative. I’ll read this out. AGI may even take us beyond our planet by unlocking the doors to space exploration.
It could help us develop interstellar technology and identify and terraform potentially habitable exoplanets. It might even shed lights on the, light sorry, on the origins of life and the universe.
Fascinating.
How about
that? Fascinating. I’m not going to say no. I think it’s great to dream. I mean. Where can this technology take us?
Um, I wouldn’t put boundaries on it. And, and as I’ve said, in five years time, we, you know, you asked me the question, where are we going to be in five years time? I said, I don’t know, but we’re still going to be at the beginning of this. You know, we’re on a journey and, you know, I think it’s going to be, you know, fascinating to see the, the sort of work, the sort of lives that our kids have and our kids kids.
Um, because it’s all going to constantly change and, you know, I probably, you know, more than many have lived through technology change, multiple cycles of it, but this one is the most profound and the most exciting.
I think profound’s the right word, absolutely. And I know, um, Peter, you obviously work with a lot of businesses.
All of the business leaders listening to this podcast are facing similar challenges around this, just trying to balance how, what their priorities are. We talked about the balance sheet for innovation, but this idea of how do I balance the need to be safe and protect my business with the need to innovate with this technology to stay ahead.
If you had one piece of advice. for a business leader trying to prioritize, what would it be?
You know, one term we haven’t talked about this morning, we’ve talked about a lot of things, is data. Because at the end of the day, this is about data. And, you know, a business leader’s got to think about many things.
But I’d throw out there that word data. Make sure you understand your data, and make sure your data’s in good shape. And, and If possible, own as much of the data as you can and understand the use cases that today you’re using that data for. And again, I love to tell stories. I love to talk about real life situations.
One of the companies, another great Aussie tech company. And I’ve only ever worked for Aussie tech companies. Um, is a company called Nearmap. And Nearmap takes aerial images of, uh, of the earth, um, built up, uh, uh, cities, uh, and buildings. And we, they, now own, own by, we sold it to an American company. They own petabyte, petabytes of data.
And every day they are flying over all the major built up areas of Australia, New Zealand, Canada and the US and with that data, they’re now realising that they can analyse and add value to their customers. If you think about insurance before or after a hurricane, you know, there are images. If you look in the old days, you’d have people climbing up on roofs, tradesmen.
To do a quote, you don’t have to do that anymore. It can all be done using AI and some super smart software that analyzes every aspect of the built environment. And that’s because quite a few years ago, they realised in addition to providing the service, they own the data and also to being able to look at.
How that data, how cities change over time. So there’s an example right in front of our nose, our nose. Um, owning the data and understanding it, I think would be, um, more than the tip. It’d be something that’s fundamental. And I think this,
this goes back to the original question. What are the decisions that a business is making today to be successful?
I think, um, Uh, look, the words go together, don’t they? Data and AI. We’re seeing new roles created, new sections within businesses, new teams, um, we talked about the popularity of Microsoft Fabric, and this is just Microsoft’s approach to trying to bring data together in a consistent fashion, but going beyond that, I think there’s a massive cultural shift that needs to happen as well, because we all become um, Data domain custodians,
if we look at, say, data leakage prevention, for example, whenever we create an artifact or something, we now have to think about the classification of that data.
Whenever there’s a culture shift like that within an organisation that impacts everybody, these are the hardest things. These are the things that take so long and some of the timelines on this stuff to embrace. And I know Microsoft is an organisation that took them a while to do this as well, because clearly they were drinking their own champagne and embracing co pilot.
And I realized that very quickly they had to have all the right classifications, their own documents, no different to our own organisation. Um, that’s a huge undertaking. It could take years for an organisation to adopt those sorts of practices. Um,
Yeah, I agree. Drinking their own champagne, that’s a great one.
I always thought it was Kool Aid. But I guess, I guess in, in this circumstance, it could be, it could be champagne. I’m going to throw back at you as you’re talking. Um, you know, this again is about cultural change and, and it’s about leadership models and that’s an area that we could talk about because, you know, I mentioned democratisation of AI.
It’s also the democratisation of knowledge. And of information and you know, in a hierarchical, um, world, in a hierarchical situation, you get grad straight out of uni or you know, kids straight outta school and they work their way up through the organisation, through the company, and they learn information.
Well, guess what? From day one, it’s, it’s at their fingertips. Mm-hmm . So I think we’re gonna be looking at. Much flatter organisations. Leaders have got to be much more collaborative. They’ve got to have much greater EQ. They’ve got to be able to adapt, they’ve got to be able to motivate people because pretty much everyone’s going to have the same access to this knowledge that in the past may have taken, um, you know, decades to, uh, to, to get hold of.
But again, Trying to invest in that, um, uh, nomenclature of data and understanding how that data sits in the company, that’s a big task, particularly as you get to bigger and bigger companies. It’s a huge undertaking, huge. But you have to do it, you think about insurance companies, think about legal firms.
You know, all of these, um, often process based companies, um, are the, the good news is they’re already adopting it. You know, I work with, uh, as you know, many different companies and we’re already trialing it. You know, I sat in a board meeting the other day where the minutes, um, the first cut at least were taken using, um, an AI product.
You go to the GP these days. And they sit down and they say, do you mind if I take my clinical notes about my life and my body on, uh, AI? And you say, sure. Now, hopefully someone with a bit of expertise checks it over. Um, but you know, daily life, work is just being changed.
You can see that in the future. I can already see a world where you’re not going to want to go to a GP unless they’ve got an AI, uh, companion.
you know, to help them get access to the latest literature.
Exactly. But then what’s the quality of the literature that they’re actually analysing? I mean, that’s a whole topic we could go through as well. Yeah, it’s a, it’s a rabbit hole. But I mean, I, I love the way that technology does good things. I mean, we know today that Machines can predict, detect cancer in many situations quicker than a doctor can.
You think about radiology, you know, where this massive amount of data is analysed ultimately today, or yesterday, visually, um, by a radiologist. Well, guess what? Today, most of that can be done and is being done. Yep. Um, and. Don’t get me started. I’ll keep going with the analogy. Well,
no, I love that. It’s the AI is a net positive for humanity.
Absolutely. I think
that’s the key. You know, there’s, there’s issues and we haven’t talked about security and sovereignty and all those things that are fundamental as well. But the upside on, on the positive side of the balance sheet. You know, some wonderful things are ahead of us.
Yeah, look, I mean, security was one of our first use cases within our own business and we’ve talked about it before, um, being able to improve, um, the triage life cycle and reduce mean time to respond and mean time to closure to as low as possible.
possible. Um, we had some amazing outcomes within our business, um, dealing with that. And I think also with an understanding that these capabilities exist as offense as well. And right. And we have to assume that, and I was asked the other day by a charity, um, they’d suffered a cyber incident about 12 months ago, and they were surprised that the cyber attacker could be so callous.
And the conversation was very simple. It’s, these things are indiscriminate and they’re programmatic, right? And there are systems and there are CICD pipelines out there looking for vulnerabilities. They couldn’t care less who you are, right? Now, clearly there’s a decision needs to be made at the time that you would ask for a ransom and determine what that ransom should be, et cetera.
Um, but the technologies are working against us and they’re most definitely helping us in our defensive capabilities.
And I think that goes back to, to the comment I made, you need a partner, you need a partner or partners, uh, who are expert in all of these areas of security and data sovereignty, uh, because the bad actors, they’re there and look, it’s an established business model, business models.
Um, and, and we mightn’t like it and they mightn’t be legal, um, but they exist. And they’re very, very sophisticated, so having a, uh, a partner who is able to run alongside you and know your business as well as you do and help you is, is fundamental. And then the whole question of sovereignty, again, don’t get me started on that.
As I said, I’ve only ever worked for Aussie tech companies, proudly Australian, and that whole question of where your data is stored, uh, and who’s looking after it. Um, particularly since COVID and that was a big wake up call about sovereignty when everyone’s scrambling for vaccines and the whole question of supply chain.
Yeah, that could take us.
And these are questions that come up in the RFPs that we respond to Jono all the time, right? We, we see this, it’s a requested thing. There’s key questions asked around sovereignty and, um, and where the data resides, et cetera. Um, so the questions are there and we expect that to continue.
Absolutely. And just going back to, uh, earlier point around democratisation of information and how that may flatten traditional business models or hierarchical structures. Um, it brings me to our subscriber question. We’ve got a graduate engineer in our hosting management center at Macquarie. Her name’s Simone.
She’s got a question for you, Peter. We’re going to listen to it now. And, uh, we’d love to hear your thoughts.
Hi Peter, my name is Simone and I’m a Solutions Engineer at Macquarie Cloud Services and a graduate of the HMC. What advice would you give me as someone wanting to develop and accelerate my career in AI?
Hey Simone, how you doing? I’ll pop by and we’ll have a chat. Someday. Look, my career, um, I’ve been in tech all my life, and the first thing I’d say is you have to be, you have to be curious, you have to be flexible, you have to innovate, and you have to be prepared to adapt. and, and grow. So you’re going to find that in AI, that, uh, the whole world is changing so quickly that you’ll need to adapt with it.
Keep your basic skills of great communication, you know, the ability to be inquisitive, the ability to learn new things. You know, we were talking here before about, um, where is AI going to be in five years time? Where is it going to be in five days time, let alone five years time? Have good basic skills, be inquisitive, and also work in a company that is prepared to invest in you, is prepared to help you get to new places.
But also remember, it’s, it’s lifelong learning. I mean, I’m still trying to work out what I want to do. in my career. You know, one day I’ll find out perhaps, perhaps not, but just keep learning.
Great advice, Peter. Absolutely. And, uh, you know, if we fast forward five years from today, what do you think a managed service provider in the tech industry looks like?
The first thing I’d say, and going back to the point I said about have the right partner, you know, you need a partner, you need a partner who’s independent, you need a partner who can be prepared to invest, and you need a partner that’s agile, travels the world.
I know at Macquarie we have study trips, and it’s one of the great things I think that differentiates us. We get on a plane, we go overseas, we say, look, we’re just a bunch of Aussies, can you tell us what’s happening? And by and large people tell you, and there are so many use cases, um, because often we are one or two years behind here, and that’s not a great thing.
Which you can go overseas, you can go to Europe, U. S., and bring back ideas. And so a managed service provider is going to be even more important in the world of AI, which is constantly changing. Looking at the new technologies, looking at how they’re deployed, giving you advice, importantly on security. And security, you know, It’s only been in the last five years that I think people, boards, have had big wake up calls.
Having the right partner on security. Knowing where your data is stored. All of these are fundamental.
Um, and I guess, in the same vein, We’d have to assume that there’ll be some new leadership roles that will exist, uh, in the next five years and due to the adoption of AI, um, what could you say about that?
Well we talked a little about, you know, new attitudes to leadership, you know, the old hierarchical structure where, you know, it’s top down, which is largely gone but still exists. Um, you know, Gen Z or whatever the new gen, they don’t like that anyway. Um, you know, it’s more collaborative, but, um, you know, we, we talked about the democratisation of knowledge where everyone has the same.
Uh, level of pretty much the same level of knowledge so that leaders today got to be motivated. So they’ve got to be more collaborative, less hierarchical. We talked about more flat structures and they’ve got to be agile. They’ve got to be, they’ve got to be a little bit nervous on their feet, constantly, uh, recognising that the way we did it yesterday is probably not the day and way we’re going to do it today, let alone tomorrow.
And it’s a good segue, I think, to the challenge that all organisations in Australia are facing and that is the desire and the need to attract the smartest talent within the organisations. And I imagine everything you’ve just mentioned there would need to be transparent and would form a basis to which an individual would want to join an organisation as well.
Yeah, look, this war for talent, and it is war for talent, um, particularly in emerging technologies. Uh, where every organisation, often a competitive advantage, is nothing more than the quality. And the ability of the people that we’ve got, um, I address the DroneShield team recently. We talked about DroneShield.
There’s nearly 300 young people. Everyone by my standards these days is young people. Um, he says tongue in cheek. He doesn’t count us in that, by the way. I, I, I’m excluding, uh, existing company. And what I said to them, you people. You know, you should be proud of what you do. You’re authentic in what you do.
You’re an Aussie company, so you’re providing great jobs for great people, but you’re leading edge tech. So, you know, to attract the right level of, uh, and skill sets, tech, tech people, we’d like to be at the leading edge. But importantly, we need to be authentic and do good things. And I was able, you know, what is obvious about Droneshare, we save lives.
You know, and, and for young people, you could just see, I said, you should be really proud of what you’re doing. And, you know, there’s a brand and Macquarie’s another one doing good things, having, um, you know, the right corporate heart, but being able to invest in new technologies.
That’s incredible advice.
And, uh, I just want to play some of that back to you. Cause there’s some. There’s some tag lines there that I think are fantastic and it’s be authentic and do good things. And I think that applies. Uh, everyone would do well to follow that advice. Peter, thank you so much. Fantastic episode. Loved your insights.
Uh, that’s Cloud Reset. See you again next time. Thank you
Peter.
Thank you guys. See you again.
What a great chat with Peter James. Uh, how lucky are we to have him as our, our chairman? Um, given everything that he’s doing, I mean, the conversation about DroneShield, for example, so innovative out there on the, the bleeding edge and doing wonderful things.
What are your thoughts?
Yeah, an incredible amount of experience. I just love these conversations and, you know, some things that I, I really love was just the, the overall positive tone, you know, of Peter’s outlook as a, as leading, you know, lots of tech companies in Australia and given his background with Aussie tech companies, you know, AI being a net positive for humanity.
Be authentic, do good things like this stuff is great. Breaking down hierarchies in organisations. This is really. Modern positive forward thinking stuff and I think that’s what the industry needs to, to get us ahead.
Yeah, I love that. And, um, obviously when we’d stopped recording, we sort of talked about belief and, um, obviously he’s got experience as a programmer and developer, but he’s done a lot of work in sales as well.
And he said very passionately that unless he really believed in something, he wasn’t able to sell it. And I, I think customers pick that up, right? If, if the belief is real, and if you’re talking about something where you genuinely believe in the value, it comes across.
Yeah, that’s right. Be authentic. Do good things.
I loved it. Yeah. Another fantastic episode.
Brilliant, okay, well look, so to our audience, um, we would say please keep watching us, um, on YouTube. There’s lots of cool shorts now as well as obviously the full episode. You’ll find us on Spotify and wherever you get your podcasts as well, Apple Podcasts, and please subscribe.
Tune in, we’ve got a raft of, uh, amazing guests coming up. We want to have you in the audience. We want you asking questions as well, so thank you for tuning in and stay with us. Yep, stay with us. It’s going to be great.
