Episode Summary
Welcome to Beyond the Algorithm, where we explore cutting-edge technology and its impact on business. In this episode, host Aarti Samani is joined by Steve Suarez, CEO of Horizon X Consulting and former Global Head of Innovation at HSBC, to dive deep into the world of Quantum AI and its potential to revolutionize industries. Steve discusses the synergies between quantum computing and artificial intelligence, sharing insights on how businesses can leverage these innovations to solve complex problems like cybersecurity, optimization, and simulation.
With over 30 years’ experience, Steve provides a grounded perspective on how businesses can future-proof their AI investments, avoid the hype, and navigate the rapidly evolving technological landscape. Whether you’re an executive trying to formulate an AI strategy or simply curious about the future of quantum computing, this episode offers actionable insights for leaders at every level.
Chapters
- 00:00 – Introduction to Quantum AI and Business Impact
- 03:16 – Steve Suarez’s Journey and Expertise in Innovation
- 05:35 – Demystifying Quantum Computing for Business
- 08:19 – Quantum AI in Cybersecurity & Fraud Prevention
- 13:59 – Quantum AI: Hype vs. Reality
- 18:31 – Should Businesses Invest in AI Now or Wait for Quantum?
- 23:02 – The Importance of AI Strategy and Center of Excellence
- 29:14 – Implementing Design Thinking in AI Strategy
- 37:35 – Adapting to Change: Pivoting & Agile Strategy in Business
- 45:03 – MBA Lessons: What Future Leaders Should Know
- 51:24 – What Keeps Board Directors Up at Night? 54:01 – The Ultimate Question for Business Leaders: Are You Creating Value?
Key Takeaways
- Quantum AI Synergy: Quantum computing and AI have the potential to solve large-scale optimisation problems and strengthen cybersecurity. However, they will complement classical computing rather than replace it.
- Future-proofing AI Investments: Businesses should start small, learn quickly, and avoid waiting for perfect data before implementing AI.
- AI in the Cloud: AI as a service reduces capital investments, making it more accessible for businesses to experiment and grow.
- AI Strategy: Itās essential to involve the whole organization in AI innovation, not just a small team. Build a culture of experimentation with clear governance. 5. Design Thinking: Businesses should adopt design thinking and engage employees at all levels to co-create innovative solutions.
Memorable Quotes
- “Quantum AI is still in its early stages, but it promises breakthroughs in fields like cybersecurity and drug discovery.” ā Steve Suarez
- “Don’t wait for data to be perfect before you implement AI. Start small, test, and learn quickly.” ā Steve Suarez
- “If the outside is changing faster than the inside, the game is near.” ā Jack Welch, referenced by Steve
Transcript
Aarti Samani : Welcome to Beyond the Algorithm, the show where we explore artificial intelligence and its impact on the way we conduct business. Today, we delve into a topic that was in the realms of science fiction not so long ago, but is now very mainstream.
I’m talking about quantum AI. The convergence of quantum computing and artificial intelligence has the potential to push the boundaries of technology and reshape industries. As organisations deal with challenges of processing large volumes of data and a lot of input signals, there is a growing need for more powerful resources. And so the promises of quantum AI are both tantalising and daunting. One report from Boston Consulting Group estimates that the quantum computing market could be worth over $5 billion by 2027. Early applications in drug discovery, logistics optimisation and cybersecurity are cited. Companies like Google, IBM and Microsoft are investing billions in quantum research. This signals its immense strategic importance.
With great power comes great complexity. Quantum AI demands that we take a brief pause and rethink our current infrastructures and strategies, contemplate whether to invest in AI technologies now or wait for them to evolve and mature. And critically, how should we future-proof our AI investments while responding to innovation with agility? To help us answer these, and many other questions, I have invited Steve Suarez to join us today on the show. Steve is the founder and CEO of Horizon X Consulting, an innovation consulting firm redefining industry standards. With over 30 years experience across consulting, telecoms, and financial services, Steve helps multinational enterprises to identify and execute new business models.
Steve Suarez : Thank you.
Aarti Samani : Steve brings a wealth of experience in leading transformative initiatives, notably as the former global head of innovation at HSBC. Steve serves as a non-executive director on a number of boards. He speaks regularly at leading tech conferences and is committed to advancing innovation. Most recently, Steve has been appointed as the corporate director of Quera Computing.
With Steve, we will explore synergies of quantum computing with AI, strategic frameworks, and innovative business model. Let’s go beyond the algorithm. Steve, welcome to the show. I am so delighted to have you here today.
Steve Suarez : Aarti, thank you very much and thank you for inviting me. And I’ll do my best to give as much as I can on this topic.
Aarti Samani : Our audience will be so pleased to hear from you. I have been getting a lot of requests to bring you on the show. And congratulations on your recent appointment as the corporate director of Quera.
Steve Suarez : Thank you. I’m really excited. I’m actually going up to Oxford tomorrow to the National Quantum Computing Center to start kicking things off. And we’ve got some really exciting news ahead. It’s a great time to be in this industry. A lot of very smart people creating. As you said, it’s very technical. It’s tough, but we’ve got a lot of bright minds working on things that want to make things better.
Aarti Samani : Yeah. Tell us a little bit about Quera. I’m curious. I’ve seen their website and it sounds amazing, but it’s great to hear directly from you what they do and where they’re taking quantum computing.
Steve Suarez : Yeah, Quero started back in 2017, and they came out of students that were studying quantum computing in both Harvard and MIT. And they came up with a modality. So a modality is a way to get to quantum computing. And there’s going to be many different types of modalities. And they came up with one where they thought that they could get to quantum advantage faster than some of the other modalities. And when people talk about quantum advantage, that means that’s the point that a quantum computer will overpass the ability of a classical computer. And understanding that is very key to understanding how you operate in quantum. So they’re based out of Boston. They are helping the UK government work on building a quantum testbed here in the UK. And I’m very proud and honoured to be part of that team to help them bring it into the country and build that for us to learn and understand how to use this technology going forward.
Aarti Samani : Very exciting, isn’t it? There’s a lot of confusion around quantum computing. I don’t, I certainly don’t understand it fully myself, and I’m sure there are many people out there like me. So help us understand in lay terms, what problem does quantum computing actually solve for us?
Steve Suarez : You know, these are things that are being worked today, but they’re really kind of four main categories that quantum actually looks to be able to solve better and they’re very specific. So I want you to keep in mind quantum will not replace classical. They are actually going to be working together. And so there are things that classical computers will always do better than a quantum computer will and there are specific very specific use cases that quantum actually will be able to provide better than classical computers. So think about things like optimisation. How do you optimise things? Pricing optimisation, portfolio optimisation, collateral optimisation. This is really big in kind of the financial sector. Then think about simulation. So think about simulating chemicals simulating or creating batteries or any type of simulation. This is where quantum really thrives and can help us to drop drug discovery faster. In that point, machine learning. So, I think about things like fraud detection and fraud anomaly. And then lastly, in the security piece, which is around how do you create more secure networks? and use quantum to actually create networks that are very hard to penetrate or almost impossible. You have to be able to break quantum physics to be able to actually break the technology.
There’s other ways that people can crack it, but through the technology it becomes much harder. And so there’s conversations around PQC, which is post quantum cryptography. I think you might’ve seen the latest news and I actually posted on LinkedIn about it, about how people are coming up with new standards to protect their encryption from these quantum computers that are gonna come in use. And then also things like QKD, which is quantum key distribution, which they’re using satellites or terrestrial means to be able to send through encrypted quantum keys.
Aarti Samani : Wow, so really important problems that we don’t at the moment have solutions for, but the threats and the risks are growing. So cybersecurity fraud, etc. Quantum computing will come in to as almost like a savior to solve those problems for us and take us forward.
Steve Suarez : That’s the aspiration, right? And so we’re in the process of creating the computers. We’re trying these things out. Keep in mind, I don’t want anybody to think, oh, this is fault tolerant, solid. We’re still at the beginning of this. And so we’re understanding the technology. We’re understanding how to apply it. People are approaching it in different manners. And so we’re in the beginning states of this. But.
A lot of companies are making breakthroughs and very big companies are making huge investments. I would say they’re betting their future on this technology. And it’s exciting to be part of this ecosystem now, right at the beginning.
Aarti Samani : Yeah, makes sense. So how does AI, as we know today, work with quantum? What is the synergy there? And how do they tie in together?
Steve Suarez : Yeah, I think this is still a field that is being researched right now. And people will tell you about AI and quantum. The reality is people are working through what that really means. The amount of AI or the use of these large language models are causing a lot of energy to be expended to be able to run this. And I think if you look at the demand on AI, and obviously it’s blown up as far as use and everybody wanting to get involved, AI, the demand on that is very, very tight. And so eventually there’s going to be more demand than there is supply. And if you keep going with the amount of use of this AI, the amount of chips, the amount of energy, will not be able to sustain the demand that’s coming through. And we’re hoping that with the use of quantum is that we’ll be able to process and apply these AI algorithms or process them through a quantum computer that will use a lot less energy and could be a lot more powerful, which means, obviously, less drain on the actual supply.
Aarti Samani : Understood. Yeah, that makes sense. So AI is at the moment, at least very resource, very resource intense, it’s expensive to run, it consumes a lot of energy. And the demand, like I say, is growing, right, more and more people are using it more and more applications are being solved with AI. And so quantum computing is setting the way for the future to replete some of these resources which are not infinite in any way and make them more accessible, more cost effective perhaps.
Steve Suarez : And that’s the goal. And it’s still yet to be done. So I can tell you that there’s a lot of hype out there. And I would say, you know, I’m an optimistic person, right? I’m, I drive innovation, my job is to look at possibilities. How do you drive these technologies? And what’s the art of the possible? So that’s the way I’m wired. But I also work with other people that kind of help tamper down the hype, which is what I need to make sure that what we’re talking about is something that is realistic and that we can deliver.
So you have to have that balance. People who have the imagination of what is possible and how I can do this versus the people that kind of keep you grounded to say, okay, well, here are the limitations, here’s what we can do. And I can see like both in AI right now, the amount of hype of what AI can do and how we’re using it versus what’s quantum and quantum coming. It’s kind of like the next evolution of everybody saying, okay, now we’re moving on and we’re gonna be talking about quantum. If you look at, there’s a good study from BCG actually that they’ve produced on generative AI back in January that said 40% of organizations are not doing anything with generative AI. And then the other 50 are just testing and playing around with it, which leaves about 90, you know, that’s about 90% of organisations. That only leaves about 10% of the organisations that are actually implementing it, scaling it, folding it into their production environments and really gaining the value of it, which I think leaves a huge opportunity for using this technology to have an impact on our knowledge workers, on the people that we have. But it also, it’s not this big thing that is saving us today, because the reality is people are still learning and trying to understand how do you create value from this technology. I would say quantum is even a step further from that.
Aarti Samani : Yeah, that’s a good segue into what has been bothering me and playing on my mind, which is when I often read headlines like quantum artificial intelligence is closer than you think, and given the promises of enhanced cyber security, better medical care, etc., it’s very tempting to get carried away with the hype. But how far are we actually from quantum computing being adopted more widely in businesses? Are we talking five years, 10 years, decades? What is the scale? Give us some context. Help us to contextualise. How far are we from it coming into our mainstream adoption life?
Steve Suarez : Yeah, well, I would say we need to separate quantum technologies from quantum computing. So I would say quantum technologies are being used today. You’re using them today. There’s a lot in the sensing. There’s things like atomic clocks. If you use your GPS to go anywhere, you’re using some type of quantum technologies. I get from a security perspective, as I mentioned earlier, you know, there are companies that are now having new protocols to combat against the future quantum computing companies or products. So that’s like PQC, which is the post quantum cryptography, where they’re protecting their assets today. And what they fear is that they’re capturing data today.
And harvesting that data later when they can decrypt that data. And that’s a very key component because you might not think, okay, well, if somebody captured my data, it’s not going to be worth much in 10 or 15 years. But I can tell you, Arti, if you went back, let’s just say we went back to 2010 and I had access to all of your data back in 2010 because now I can decrypt it, would you feel comfortable with that? Right? No.
Steve Suarez : And so I think really understanding and understanding what the technologies can do today. And these are things we have to start working on today. Now quantum computing is a different dynamic. And depending on who you ask, and here’s the problem with it, is nobody really knows. Everybody’s talking about making breakthroughs. There are companies that are saying they’re going to make breakthroughs by 2026.
There’s a lot of companies saying by the end of this decade, so by 2030, that we’ll get there and their roadmaps all show that they will. I’m making a bet that somewhere in the 2030s, this will happen, but it’s not, I’m not waiting for that to happen to start working on it and understanding it. And so that’s why I’ve made a bet or commitment into this to really start understanding it and working on this technology.
Aarti Samani : Yeah, yeah, that makes sense. We are still getting our heads around AI and generative AI as we know it today. And there’s already pressure to be preparing for a quantum future, right? So there are terminologies or acronyms floating around like a QRI index, quantum readiness index, reports that claim high ROIs for QROs, quantum ready organizations. This is all a bit too much for the business community, at least where I’m plugged in. And the classic question is, if I invest in AI infrastructure in my business now, today, given how quickly AI itself is moving, will I then be left with some costs and…not gain from quantum advancement. So at a very basic level, the comparison you can draw is with mobile infrastructure, right? So countries that invested in mobile infrastructure are now behind in rolling out 5G, whereas the ones who didn’t invest in the infrastructure can leap forward. So is it the same here? Should I be holding investing into AI today as a business leader? Because in two years, three years, five years time, there will be another leap change, not even step change, a leap change, and therefore my investment will be redundant.
Steve Suarez : No, I don’t think so. I think a lot of things have changed before. When you actually have to get into technology and your comment about mobile and telecoms, there’s a lot of capital investment that has to be made. So it’s very capital intense to get into that market, to start getting engaged. And so the good news is about the technologies that we’re using now, both on the AI side and on the quantum side is that they’re leaning more to cloud-based.
So you don’t have to make those capital investments. You could use AI as a service, cloud as a service, well, quantum as a service, and you don’t have to pay out those capital outflows to make these bets anymore. And so the good news is the way the model is, is that you can start experimenting, you could start working on these things and used it.
And as you learn, you can build more and more commitment on some of these technologies. So I don’t think we have those big infrastructure bets that we have to make. We can get involved. I wouldn’t tell anybody to wait to do anything at AI. I think I do hear some of my clients tell me, oh, well, we’re not going to do anything with AI until all of the data is perfect.
And the reality is your data will never be perfect. And so if you’re going to wait till your data is perfect, then, you know, you’re never going to get it done and your competitors are going to use AI to lower their costs, increase revenue and to get ahead. My suggestion typically is get in, get involved, start learning, make small investments, and then as you make these investments and you learn, then you can pivot to decide, you know, how do you want to use this?
So make it very quick, make your learning quick, make it frictionless and make it cheap so that if you do make a mistake, you can pivot very easily. And I can tell you, nobody knows the right answer from day one. So everybody’s going to be going through the same process where they’re going to have to pivot, they’re gonna have to learn and do this. And this is the right time. There’s many services out there that are offering this technology as a service. Typically, it’s funny that dynamics is before it would be the big organizations that had the big budgets to be able to use this technology. But now this technology is in the hands of the users. So the users are using this technology.
So, you know, it’s a different dynamic because now organisations are in the back foot and like nobody, there might be a policy in my organisation to say, I can’t use this AI, but I could tell you as a user, there is no problem. I can use the AI and work that out. There is the governance side of it, which is a different conversation that organisations do need to govern and make sure that they’re managing it well. But I think don’t wait. The reality is get out there, test, learn. That’s what I tell everybody, test and learn. The faster you can make test and learn, the easier, the cheaper, the more you’ll stay ahead. I like there’s a quote from Jack Welsh that says, if the outside is changing faster than the inside, the game is near, or the end is near, sorry.
Aarti Samani : Yeah, that’s quite profound. And in this case, the outside is definitely changing faster than most of the insights, right? And you make a great point there that if, as an organization, you have a policy to not use AI, be sure that your staff are already using it in their personal time. And it is going to infiltrate into their work life also. So it’s better to officially allow, test, learn, introduce AI, but then govern it. along the way.
So how should we go about thinking strategically? So I’m a business owner, or I’m an executive in a small to medium-sized enterprise. How should I go about thinking through an AI strategy? Do I need to install an AI center of excellence in my small organisation?
Help us guide us through that journey, Steve. What should I do? How should I go about thinking through an AI strategy, formulating it, and then implementing it?
Steve Suarez : Yeah, no, the listen, having a group that can, if they wanna call themselves the center of excellence, is great and it makes them think, you don’t wanna think that it only belongs to a small group. So I’m really a big proponent of open innovation, giving everybody access to it. And so when you talk about AI, you want to engage your community, you wanna engage your employees, you wanna engage everybody.
But you do want to put those guardrails to make sure that it’s being used right. And so what I would probably say is, yes, get that community together, have somebody that understands the technology and that can create these guardrails so that you can engage people to participate. And I think the first part, which is kind of what I mentioned, was test and learn.
People learn more when they get their hands on things, not when people are talking to them or they’re reading books, when they get their hands on some of these technologies and apply some of their ideas. So do experimentation and do it in an area where it’s like a sandbox or a bunker so that you’re not affecting production, your mistakes or failures don’t impact anything. It’s in a protected area so that I can try out a hypothesis that I have on doing that.
And so, you know, let me work with somebody that understands this technology, because we don’t need everybody to be AI experts. And let me bring my ideas to that team and that team can help me build it and do the environment. The other thing is identify the value. A lot of people want to do proof of concepts or experiments just for the nature of I’m using AI.
But if you’re using AI and you’re using it well, but it doesn’t provide any value, then is it somewhere you really want to focus on? So make sure you understand what is the value and who are you providing the value to? The reality is a lot of organization, and it’s odd. I’ve never heard so much of what I’m hearing now where people’s like, I need to do an AI project or I need to do an AI, a generative AI program. And…
Steve Suarez : And when I ask, well, what is it that you’re trying to solve or what are you trying to do? It’s like, no, I just need to get AI into it. Instead of starting with the problem and finding out what problem you’re trying to solve and then going to the solution. People are going right to the solution without really understanding what that solution is gonna do for them.
Steve Suarez : And so I’ll go through quickly. So it’s test and learn, identify the value, create readiness. So readiness is creating training for your people, making sure that you can help them upskill. And upskilling is key. And some organizations see that upskilling as an expense. It’s truly an investment to your people. You want people that understand this technology, that want to learn and make it self-pay so that they can do it on their own.
Make sure you establish a governance, and this is key, because you want to say, okay, we want to be fair, we want to be ethical, we want to make sure what can people use and what they can’t use. You do not want confidential information being put into these LLMs that go outside of your organisation, and that could be used to train other people’s models on your data.
And so you got to make sure you have that governance piece on it. And I can tell you, there’s a couple of companies that have done this wrong. Um, there was one company that used AI to, to play chess and you would think, okay, well, that’s pretty harmless, um, building an AI to play chess, but they did it with a robotic arm. And when the kid went to just touch the other, um, uh, person’s, um, chess piece, the, the robotic arm came down and broke the little kid’s finger, because they didn’t build that safety into that process. And a couple other, I think I wrote an article, well, I wrote an article about a truck for a buck. There was a truck, a Chevy Tahoe, that was sold for $1. And this truck’s about $77,000 because a chap bought, made a deal with somebody and they knew how to get what they wanted. And there was a deal.
I think, I don’t know if you’ve heard about Air Canada, they ran into something where they were trying to say, well, our chat bot doesn’t represent us. And they were trying to disavow their AI, which really didn’t work for them. So test and learn, identify value, create readiness for your organisation, and make sure you have the right governance is a good start on how you can get out and create this for your organisation. Does that make sense?
Aarti Samani : Yeah, yeah, it does. It’s a great four step process and framework that people can take away and use. And it’s amazing how many times I hear what you described there, start with the solution, and then figure out the problem. So just because AI is all around us doesn’t mean we stop using natural intelligence in favour for artificial intelligence, right? You still have to don’t forget your don’t forget where to start the basics of one-on-one of strategy. Design thinking, right? How are we going to design this thing? What once we figured out what problem we’re solving, how are we going to design the path to that solution? So we when you and I first connected, we talked a lot about design thinking as a core part of strategy formulation. So how do you go about implementing some of that design thinking into the work you do with your clients?
Steve Suarez : But one of the things that we do is we start with a design thinking bootcamp. And so we do like a two day bootcamp and that bootcamp we asked that the senior management participate in that bootcamp. I’ve often seen that we do training sessions and we train all different levels of the organisation. And the one common thing I hear was like, wow, that was a fabulous training. Only if my boss would go to it or only if the management would go to it, we could really make a change. And so you have these people at different levels of the organisation seeing the value in this, but it wasn’t done holistically, it wasn’t embedded as a culture. And so one of the things to really try to embed this as a culture and understand is, you know, getting the senior management on board. I can tell you, if your senior management isn’t fully on board and understand this, it makes it much more harder. And I would say, I wouldn’t even go through the effort unless you have that executive buy-in. So doing a two-day bootcamp so that people understand the methodology of design thinking, understanding the iterative approach on how that can be more valuable and how that can get you closer to delivering what your customer wants instead of what certain people think your customer wants, and applying that and then doing a training session to the rest of the organisation. It doesn’t have to be a two-day dedicated bootcamp, but it could be what we’ve done in the past is like a four-hour course explaining what it is, talking the same terminology. And then talking about wins. How have you applied those methodologies to create wins? And that starts developing this maturity and confidence within the organisation that I’m using these techniques to deliver real results to the organization. And I’m a big believer, as you are, in design thinking. I think people are maybe saying some of the terminologies without fully thinking, without really using it. And I think I’d like to keep pushing that methodology and that structure on how to drive things forward.
Aarti Samani : Yeah, no, thank you for that. Working from first principles is the most overlooked activity in strategy formulation in business at the moment. So you gave us some examples of where AI has gone wrong when it hasn’t been fully thought through. Can you give us one or two examples of where it has been actually deployed of in a proper way and has delivered return on investment for those organisations.
Steve Suarez : Yeah, you know, there’s a company I’m working with right now that’s doing conversational AI. And they do most of the voice work globally for big companies. I know that one of them is like FedEx or they do things for hotels. And I’m very impressed with the amount of natural language that some of these conversational AI companies are doing and what they’re able to solve. And I often hear organisations saying, look, our default, our rates of people hanging up or not being able to solve problems is gone up because some people have gone off sick or something. And that causes a ripple effect throughout their organisation. So if your first purported event tree is not a good, great experience and I can’t solve it.
then it gets a lot more expensive to solve that person’s problem as they go up. And so conversational AI is one of those where we’ve been able to see that AI can solve people’s problem without having to talk to human. And sometimes the things they’re calling about is the same thing, the majority of the people are calling about and it could actually help you think to say, okay, why is everybody calling us about this one thing? Maybe we need to fix that one thing so that we can solve it and address it because people aren’t really understanding it well. And so, I mean, call volumes, lowering cost, increasing customer satisfaction by percentages. And I’m seeing both on the cost side, but also on the loss revenue side.
And so this isn’t just a cost play, it’s an increased revenue play where they’re using this technology. And if you haven’t seen it, the company I’m talking about is Poly AI. They’ve got on their website, you can go to their resources and you can listen to some customer calls. And I could tell you it’s incredibly impressive the type of work that they can do. So they have these big percentage changes in how they’re able to add value.
And I’ve seen it firsthand. So that’s kind of one example. There’s a lot of other examples too. There’s one company, I can’t disclose the name, that takes documents and they ingest the documents in one language. And because English isn’t their first language and they have a corporate headquarters in here, it’s hard to kind of go through some of the regulatory governance papers that come out, you know, these papers are very long, or they want to interrogate it. And so they feed these documents into this model, and they’re able to interrogate those documents in their own language, and they’re able to ask questions. So imagine you uploading a PDF, and instead of having to read the whole PDF, you’re asking questions that you want to see are in this PDF, and you can actually interact with the document and it’s answering you back. And it’s doing it in another language that’s not your own language. So those are just some of the examples that I’ve seen that have been pretty powerful. And I’ve seen my clients actually smile and get excited about it.
Aarti Samani : Yeah, yeah, no, those two are great examples. And actually the first startup I worked in London, a company called SwiftKey, we did natural language processing to predict the next word, the next phrase in hundred and something languages, 150, 180 languages, I think. That was about 12 years ago, a long time ago now. And even at that point, NLP was doing a really great job on identifying putting context to the word, but also translating and transliterating into different languages. So really powerful examples there. How do we, so I was reading an article recently that talked about imperfect strategy and you touched upon this briefly at the start of the conversation that don’t wait for data to be perfect, don’t wait for everything around you to be perfect, it never will be. Just embark on this journey and start making the transformation slowly but surely in your business. So when we are talking about imperfect strategy as a way forward in uncertain times, there is so much flux, right? The geopolitical conditions, the economic crisis, the promise of a better future with technology, etc. The semi-annual cadence of strategy and planning just doesn’t hold anymore in my opinion. The unknown unknowns are so many that it compels us to tap almost into the serendipity of non-planning, right? So how do we go about, how do we work on sustainable business models that stand the test of time and that stand the…They stand the changes that are moving so quickly.
Steve Suarez : Yeah, I mean, I think if I come up with one word, it has to be adaptability. You have to be able to adapt. I remember early in my career thinking about, oh, I want to start my own company. I want to do my own thing. But I have to come up with the perfect idea. And everybody thinks they have to go out there with the perfect idea. And it’s funny, I studied I wanted to study how entrepreneurs thought, and what they did. And I took a course at Stanford University that I saw a lot of people come out of Silicon Valley and just do these really crazy stuff and come up with these ideas. And then, I started hearing this word pivot, right? And for me back then, it was such a magical word to say, oh my God, I can pivot. You don’t have to have the right idea. You don’t have to know everything right at the front to move and start something. And the ability to know that you have the ability to pivot. Nobody is stuck and saying, all right, here’s your business plan, it’s written in stone, this is all you can do. That just won’t work and it’s never realistic. And you think about every organisation that has been completely successful in what they do, they’ve all pivoted, they’ve all moved. The idea they started out with isn’t the idea that they’re doing now. I mean, look at Amazon. What did Jeff Bezos start off with? A website, he went out and got books and then shipped those books. Now they’re just an amazing logistics organisation. They’re a big cloud organisation. They’re a technology organisation. And part of it is really learning on how to adapt, how to change and to do that. And it’s not easy, but…I think if you have those experiences and you’re in those tough situations, you can use your past experiences to do that. And as a board member, and I know you and I were at a board member organization here just recently, it’s even more important because not only are you having to understand things like cyber, AI, ESG ratings and stuff like that.
Steve Suarez : But your ability to influence, to get that done, the day to day is very difficult because you’re kind of stepped away. So how do you get held accountable to something that you can only influence or oversight and govern? And so I think, you know, it does get difficult. And I think we need to be adaptive. We need to be curious, and we need to constantly challenge ourselves to learn and understand these new technologies, not just pick up.
You know, I heard this person say this, so that must be what it is. Cause a lot of times, you know, what you hear may not be fully, uh, what’s really going on or what are the capabilities. And I think we’re hearing some of this stuff in the technology height that we get today.
Aarti Samani : Yeah, I think leadership is so difficult at the moment. It’s probably one of the most challenging times to be an executive senior leader in business, trying to lead your people, keep them reassured, calm, focused, motivated, but then knowing that there are choppy waters ahead of you and very uncertain terrain that you are walking through. So that’s interesting. What do you think?
Some of the business models will evolve as we move forward. So when I say business models, I mean charging structures, revenue structures, et cetera. I’m already seeing some of the AI products, like these SaaS-based, cloud-based products, are offering almost like a day rate of AI, right? So until now, the day rate was limited to human consultants who would go in, solve a very specific problem for 24 hours, and come back or a working day and come back. And I’m now seeing a day rate for AI, so you can actually sign up for these tools for one day to solve a very specific problem, and then you don’t have to pay a license fee or a subscription fee, et cetera. So it made me chuckle, it made me think, actually, what kind of business models do you think will start to emerge as we move forward?
Steve Suarez : Well, I think you look at the gig economy, you look at kind of the pay per use. And you’re absolutely right. You talk about day rates. There are hourly, they’re down to the minute. And there’s actually now you can use consumption on cloud down to the second. And, you know, and so looking at different charging models and understanding how that operates could change business models altogether.
Before, if you were going to start a business, there would be a lot of upfront costs, a lot of capital expenditure that you had to create environments, boxes, equipment. If you wanted a project, you had to say, okay, I’ve got to order X amount of boxes and it’s going to take me six weeks to deliver. And then I’ve got to install the software, I’ve got to do everything, we’ve got to go through committees. If you want something up and running today, you could just go out there, go to a marketplace download the software you need, get the environment up and running with the exact specs you need to, and you can get people working within minutes. And I think that is key and it’s a lot more rapid. And you’re right, I think business models are gonna change. I think the platform and economy is big and you look at the most valuable organizations are creating platforms and kind of integrations into their ecosystems that will have an impact. And I think understanding those business models, understanding how you can make things more accessible, more affordable will be key because that’s kind of what people need. People don’t need to buy a machine that’s gonna sit there and be idle for 60% of the time and only be used the 40% of the time while other people could be using that. And so I think that there’s a lot of very interesting models in the whole as a service, if you will, economy.
Aarti Samani : Yeah, so optimising resources and passing those savings in your charging structure to your clients. That’s an interesting way to look at it.
I want to just change tracks slightly and go into an MBA class. So you have a lot of association with academic institutions, right? University of Oxford, Harvard, MIT, etc. And I’m a big fan of academia as temples of learning. I work with Durham Business School myself. And when I speak to the MBA students there, I wonder if we are teaching them the right curriculum and really preparing them to be the future leaders that they aspire to be. So what do you think we should be teaching our MBA students today?
Steve Suarez : Well, I think we, I like maybe a bit off track, I like the fact that we are teaching ethics and that there’s a class specifically on ethics and understanding because I think we need people to understand the impact that they have, the impact to society and our responsibility on the things that we do and so, it’s not only about how much I can make the shareholder, it’s how I impact the community and being more holistic in that I think is gonna be key that we provide rounded individuals that is not just incentivised by the financial part of what they’re doing, but what is their impact to society? How are they helping drive things forward?
I think, you know, I like the case method. Harvard teaches based on the case method where they bring out a case. The case isn’t there to tell you what’s right or wrong. It’s there to have you debate. It’s there to have you see different points of view. And I could tell you that sometimes I’d be in a class, I’d read a case and I’d go in with a very specific, I know the answer, this is the right thing.
And then all of a sudden having conversations with other people that I respect a lot, I love their point of views, completely different than my own point of views, opens my eyes to say, wow, I’ve never really saw it from that perspective. And I understand why that would be important and kind of working with them. And so having this constructive conflict where you can be professional, you can have a different point of view, you can debate things will open people’s mind. I think we need more of that. I think there’s too much of, I know the right thing, I don’t wanna hear anybody else’s opinion and working on that. I think if we can get into environments where we can have really good in-depth conversations, understand people, understand points of views, we could really drive things forward. And I think the good thing about these schools is they understand that, that…provides a lot of different, it helps you understand how to debate, it helps you how to get your point across. If you can’t get your point across, you can’t influence people. If you can’t influence people, you’re not gonna be successful. So there are certain traits that it helps you develop as a student to help you prepare for a working life. So that’s kind of what comes to mind. I’m sure there’s plenty of other things. I like you love education.
I’m constantly challenging myself to learn new things. And I think these institutions are just amazing and of what they have to offer. And they’re being challenged and they’re being disrupted themselves. And they want to change and they want to find how do I provide this and make it more accessible to more people, not just a privileged few, if that makes sense.
Aarti Samani : Yeah, absolutely. That key skill of teaching our young people to analyze from first principles, going back to what we were saying earlier, right? Go back to first principles, think, analyze, and then make a decision versus ingesting what you already know and then closing your minds to new ways of solving a problem which will be critical going forward. So these leaders will need tomorrow. What kind of leadership positions can they expect around executive tables? Do you think our executive teams will change their composition and their structure? So will we see chief AI officers around the table temporarily or more long term or will we not see them at all?
Steve Suarez : Yeah, you know, I think it’s a good question. I think job responsibilities will change. I think there’ll probably be more demand on business people to be more technically oriented. I would say even on the technology side, there will be more demand for those technology people that want to move up to be more business oriented as well. What is it the value that you’re creating? Don’t just focus on the technology.
One of the things that for me, I found really impressive in some of these studying was understanding even the financial acumen, understanding how for a technology person, how to read an income statement, how to read a balance sheet and understand where things are going, being able to predict or stopping things that you know, if they continued on this path.
And sometimes just looking at a balance sheet, looking at income statement, looking at some of the financial statements, if you know what to look for, it can be very insightful. And I think having that good balance of being able, because the days of, listen, I’m only gonna be a specialist in my area and that’s all I care about, just doesn’t work anymore. You have to be able to go across the organisation understand other people’s point of views and see things from their perspective to see how things operate.
Steve Suarez : So I don’t know if I fully answered your question, but I think job titles and job responsibilities will constantly keep changing. Will there be a head of AI? I don’t know. Will there be prompt engineers? Well, there already are, but is that what they’re gonna be? Or prompt engineers, somebody that can ask questions. That’s kind of what a prompt engineer is, right? Somebody that can ask really good questions so they can get good outputs.
Yeah, I’m sure there’s going to be a change. I just, I personally don’t know exactly how it’s going to change, but I’m preparing myself to be adaptable, to be able to respond to that change.
Aarti Samani : Yeah, yeah, no, that makes total sense. So what, going back into the boardroom then from executive table into the boardroom, in your experience and given your, the board work that you’re doing today, what is top of mind for chair people and board directors at the moment? What’s keeping them awake at night?
Steve Suarez : Well, I think top of mind, keep in mind when I actually, I wanted to be a really good board member and I actually went back to school to study this so that I said, look, if I’m gonna do this, I wanna make sure I do it right. And so I went and did the CDC, which is the corporate director certificate. And there were kind of the four main good governance committees, audit committees, compensation committees.
And you think, okay, well, you encapsulate everything there. But the reality is boards today have a lot more demand put on them, a lot more challenge. And think about things like cybersecurity, data leaks, AI, ESG reporting, all of that has now been put onto this board team’s responsibility. And it keeps growing and the responsibilities keep growing. And so finding out, you know, how do you provide that good governance? How do you become that good board member? Because we’re all hearing about these organisations that fail miserably and you think, well, what was the board thinking? How were they managing that? And you would think that, okay, well, that will never happen to me because I would make different decisions as a board member. You’d be surprised on what could happen. Or if you did something wrong and how things can go wrong. A lot of these board members that sit in these big organisations that aren’t going well are very smart, very dedicated people, but these things happen. So what keeps me up at night is, you know, thinking about, you know, some of these responsibilities and how I can cover it and how I can be, continue to be a good board member for the companies that I sit on their board.
Aarti Samani : Yeah, okay, well, thank you for sharing quite a lot of information there. Steve, we’re approaching to the end of the show, and the one question that I ask all my guests is, as we move beyond the algorithm, what is the one question that leaders at executive tables and in boardrooms should be asking, but are not?
Steve Suarez : Yeah, what is the value that you’re creating and who are you creating it for? That’s what I would say. If you’re using AI, using this technology, why? What is it that you’re trying to achieve and make sure your intentions are clear so that you know you’re delivering it? It’s like, how do you know if you’re winning if you’re not keeping score? And I think…we can all get caught up in this AI algorithms, technology stuff. But at the end of the day, all of that doesn’t matter if you’re not providing the value. So focus on value and what value and to who you’re providing it to, your customers, your employees, the stakeholders, and then focus how are you going to provide that value. Don’t go straight to an algorithm is going to solve that for you. I mean, I think that’s, it’s natural,
That’s kind of my view.
Aarti Samani : Yeah very good. Again, going back to the why, asking the questions, going to the first principles, design thinking, all the things that we covered are exactly what senior members in our business world should be thinking about and taking action on. Steve Suarez, thank you so much for joining us today. I have had an amazing time. I could go on and on. This conversation could carry on for much longer, but we are out of time. And I really want to thank you for giving us your wealth of experience, your insights and your time today. Thank you.
Steve Suarez : No, thank you very much, and I really appreciate it. And keep up the great work.
Aarti Samani : Thank you, Steve.
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