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Rise of the machines, with Rik Reppe & Anand Balasubramanian
60 Plays9 months ago
AI is already having a seismic impact on organizations and wider society. And we are barely even scratching the surface of its potential. But the technology is only half the story. The organizations that will thrive in an AI-driven future are the ones that can apply AI tools intelligently to solve customer problems.
To understand the possibilities, the pitfalls, and the applications of AI, host Will Kingston is joined by the co-leaders of Acquis Cortico-X's AI practice, Rik Reppe and Anand Balasubramanian.
Follow Acquis Cortico-X on LinkedIn here.
Contact Rik: rreppe@cortico-x.com
Contact Anand: abalasubramanian@cortico-x.com
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Transcript
Introduction to Aquas Cortico X and AI Prom Analogy
00:00:00
Speaker
Aquas Cortico X is an experience-led transformation business that partners with clients and technology companies to drive digital acceleration. We are experienced activists, passionate about elevating everyday human experiences through the belief that what's best for people is what's best for an organization. Reach out to us for a chat. A link is in the show notes. Now, cue the jingle.
00:00:37
Speaker
Hello and welcome to Speaking from Experience, from Aqua Scortico X. I'm Will Kingston. There was a quote that did the rounds when big data was all the rage. Big data is like teenage sex. Everyone talks about it. Nobody really knows how to do it. Everyone thinks everyone else is doing it. So everyone claims that they are doing it. I think AI is more like the prom.
00:01:04
Speaker
Everyone is excited. Some people think it may even be life changing. The people in charge have a nervous feeling that it could end in disaster, but really no one quite knows what will happen. Oh, and as there is often teenage sex after the prom, everything we said about big data applies to AI as well.
AI's Transformative Potential and Comparison with Past Tech Trends
00:01:23
Speaker
To help me understand the potential and pitfalls of AI for organizations and wider society, I am delighted to be joined by the co-leaders of Aquas Cortico X's AI practice, Rick Repi and Anand Balasubramanian. Rick, I'll start with you. You've seen several technology crazes come and go throughout your storied career. Is the hype around AI justified? Yeah.
00:01:50
Speaker
It is. As long as you keep it at the AI level, right? If you think, just think back two years. NFTs. Oh, NFTs, man. Like everyone needed NFTs. We were all embarking on NFT strategies. We fielded so many calls about NFTs. And about the same window of time was metaverse, metaverse, metaverse, metaverse, metaverse, metaverse, metaverse.
00:02:12
Speaker
What's different about AI is AI is the concept, right? It is the underlying thing where with NFTs or with crypto, if you carved away NFT and crypto and you thought blockchain, oh my, that is game changing. NFT, crypto, those are applications of the thing called blockchain.
00:02:35
Speaker
Metaverse would become the manifestation of virtual, augmented, mixed reality, the convergence of the digital and the physical. That's a big deal. And you don't have to create a true metaverse to be taking advantage of that. AI is the same way. So if you were to say, check GPT, and they've certainly come out of the gate, great.
00:02:58
Speaker
haven't they, right? Like they're very successful, but chat GPT versus artificial intelligence or in that case, generative artificial intelligence. Artificial intelligence fundamentally allows us to do things at a pace and at a scale that we've never been able to do before, not even come close
Understanding AI: Terms and Outcome-Based Design
00:03:17
Speaker
to before. That is in fact transformation.
00:03:20
Speaker
Whether or not chat GPT, you know, in two years, I don't know if it's still going to be chat GPT or Gemini or anthropic or insert company that we don't even know exists yet. But generative AI creating something, sentience essentially, where there is no current sentience, that's a pretty big deal.
00:03:38
Speaker
And Andrew threw out a couple of concepts there. We heard AI, we then heard generative AI. I also hear machine learning. I hear about deep learning. I think this is one of the problems because if you're not tech savvy or data savvy, it is actually quite difficult to get your head around this and the umbrella of terms that AI encapsulates. How do you think about what AI is and perhaps what it isn't?
00:04:03
Speaker
Sure. So, you know, the easiest and best way to think about this is figure out, like, what is that end user experience you want to deliver? Right. So if you can figure out the end user experience, then think of AI as the tools or the means to get you there. Right. And the reason why is, you know, most of the times what people say is that
00:04:22
Speaker
I want to use AI and they don't know why they don't know what problem they're trying to solve. They just want to use AI because it's cool. So let's take chat GPT itself as an example, right? So let's assume you want to do wedding planning, right? So now you say that what are you looking for and then have chat GPT help you plan that thing. What aspects of it is it planning? So there's an outcome associated with it as opposed to if you just go to chat GPT and say, well,
00:04:49
Speaker
what should I do for a wedding? It's going to give you a response and you're just going to be like, none of this makes sense. I think that's the biggest difference. When you think about AI, think of AI as there is different types of AI that's there. These are all tools in a toolbox that actually you're putting together in a particular way to drive an outcome. But without knowing the outcome, you don't know what you should be stringing together and how they should be orchestrated.
00:05:17
Speaker
That's indicative of something that we see from a lot of the clients that we're working with and talking to. And it's exactly the point you brought up in the question. It's, I don't really know what AI is, but I'm a business leader and they'll call us and they'll say, we need AI.
00:05:33
Speaker
Yes, you also need oxygen. Can you perhaps be a bit more clear?
Aligning AI with Business Goals and Early Business Integration
00:05:38
Speaker
And I'm not actually saying that as glibly or meaning that as glibly as I said, it's I'm a business leader, man. AI is big. It is a big, complicated topic. What I can see is that it can really make a big difference. How should I think about it? And as Anant said, what do you what do you need to accomplish? What are the business challenges you have? Then let's figure out
00:06:04
Speaker
what kind of AI or AIs may be able to help you in service of a particular goal, as opposed to we got to get AIs like, okay, I mean, let's re-platform your company just for starters, which may not be the right you want to go down. If you're not clear on what's the outcome going to be? What's the application going
00:06:24
Speaker
I think this is a wonderful insight that both of you have hit on. So many emerging technologies are a hammer in search of a nail and getting to the customer strategy first of what does the end user experience look like and then saying, how does the technology help you enable that is really critical. We will get to the business applications for AI that you mentioned, Rick.
00:06:46
Speaker
bit later, but before we do, a few more prefacing questions. To use a sports analogy, Rick, what stage of the game are we at in terms of AI in its application for business?
00:06:59
Speaker
Let's make it more specific. Let's say it's a football game, an American football game. And you think about the very start of the game, then back up from that about six months to the NFL draft, and then back up from that about another month and a half to the free agency period, and then back up from that about four weeks to the actual closeout of the previous season. We're about a week into that part.
00:07:26
Speaker
Anand, you're speaking to senior leaders every day about this. To use a hackneyed phrase, what are you hearing from them with respect to their hopes and fears about AI? Yeah.
00:07:39
Speaker
So, you know, I think Rick called this out a little bit before, right? So most of the senior leaders want to be on the AI bandwagon. They don't know what that is. They feel like it's powerful, but they don't know what to do with that power or what to do with that tool, right?
AI Risks: Hallucination, Ethics, and Importance of Data Accuracy
00:07:55
Speaker
So think of it like you have this power tool, you're very excited, it's new, it's shiny, but I don't know what to do with it. It's too powerful. Can I handle it? What do I do? What if I do something wrong?
00:08:03
Speaker
And most of their concerns ends up becoming that, right? So it immediately goes from, oh, I have this tool and I can invest in two. These are the 10 things that I think can go wrong. So should I really even do anything about it, right? And their mind goes from kind of taking the same like the football analogy goes from offense to defense so quickly that now what they've done is they have actually just narrowed the scope of what AI can do, right? I have seen like companies say like,
00:08:32
Speaker
We have an AI powered engine that does this, like the small search that happens, right? And you see like, so who uses it? That's great. Like what's the kind of output you get? And you notice that these are very simple rules-based engines that you did not need AI to do it. You've just narrowed the amount of data it can leverage and what it can do just so you can say it's AI powered.
00:08:53
Speaker
I think from my perspective, leaders kind of have to open up their mind, think more about like, you know, what can I change? How can I be more transformative? And then understand that AI is not going to work in silo. It's going to be part of the strategy, right? It's embedded as part of your strategy. So you're leveraging that to now make your strategy a lot more transformative to get to the outcome quicker to test into it. And that's what's going to be the difference.
00:09:19
Speaker
Love how you're getting to the opportunistic side of AI, but let's go back to the start of that answer where you looked at the risks of AI and you're right to say that a lot of CEOs instinctively are risk averse and they see a lot of potential risks there. I'll follow up with you Anand there. What are some of the risks or the threats that you're hearing from business leaders that AI potentially will present?
00:09:41
Speaker
Yeah, so I think the two biggest ones most senior leaders are worried about is this concept called hallucination and ethics right or bias. So hallucination is this thing where it produces an answer because remember how AI is it's always going to give you an answer to your question.
00:09:59
Speaker
to the best of its knowledge. But that doesn't mean it's accurate. It doesn't mean it's 99% accurate. It could just be like 50% accurate. It could be like 10% accurate, right? Because it's just taking data based on your question. It's telling you an answer.
00:10:14
Speaker
What leaders are really worried about is that, how do I differentiate what's an accurate answer and what is not? Like, you know, if it's telling me the truth or not, because if I'm going to need a human or a subject matter expert involved all the time, then is it really providing me that productivity gain, right? So that's one. The other ones are on ethics, and that's a big deal because I think what happens is that everything comes back to the data that is fed in.
00:10:38
Speaker
Would have probably seen the news like google had this with Gemini and all where you know you ask questions about you know world war heroes and it gives you its perception of who world war heroes are or like its perception of boardrooms and i think it did this give a perception of a boardroom of all just white males.
00:10:57
Speaker
And it's not a fault of Gemini by itself. It's just the model is not trained or has had that kind of data. It's more that that's the data it's fed in and that's what it's interpreting. But now you don't have this human filter that's looking at it saying, well, that's what I would have gotten to. But I'm not going to say that because that's not the right thing to say or things have changed. I'm going to look at it, take a step back, or just say, I don't know.
00:11:22
Speaker
and is not going to do that it's going to say i got this that's the answer there you go because it's not able to differentiate that emotional component. I'm glad you use the term hallucination and hallucinating it's such a wonderfully romantic term. The AI hallucinated and it points out one of the challenges of AI from business leader perspective which is like how to come up with this answer.
00:11:45
Speaker
Like, even if I believe it, how to come up with it, it's like the genie. I asked the oracle at Delphi and the oracle said X. Well, the oracle at Delphi was wrong a few times, even back in Greek mythology. And it makes it sound mystical and mysterious. It was wrong, right? Sometimes that's because it's trained on data.
00:12:08
Speaker
that either was incomplete or it ended three years ago and things have changed in that period of time. So that's a mistake. But other times is AI just wants to give you an answer. Like it's that teenager.
00:12:20
Speaker
that you ask a question to who has no idea what the answer is, but wants to sound smart. And it's like, uh, uh, uh, and unfortunately AI doesn't do that part, the uh, uh, uh, where it's like, if you pulled up to a curve and you said, Hey, how do I get to this particular restaurant? And someone started out by saying, um, um, you'd like pull away.
00:12:42
Speaker
Like you just need to keep driving and go ask somebody else. And so it will just make up an answer based on ultimately the median internet answer. That's essentially what it's doing by scraping all
Embracing AI: Overcoming Fear and Exploring Generative AI
00:12:54
Speaker
that data. But as a business leaver, then you've got a problem. You can either be so afraid of AI that you don't use it, which is a really good way to get left behind. Or you can figure out how you can use it and kind of trust but verify.
00:13:11
Speaker
right, and put in the processes and the programs in place to be able to come up with that. Bias is a rough one, right? It's just hard because what's the media and internet answer to any question, not as we tend to think about it. In the country we live in, it isn't scraping in the country that we live in. It's scraping the internet as it pertains to planet Earth.
00:13:40
Speaker
It's not just the data inputs. It's also the algorithms that are created by people that then guide AI. So if we look at the Google Gemini example, Google did get into trouble recently or courted controversy because the responses that the Gemini platform was giving were perceived by some to be highly politicized and going in one direction. The reason for that it was inferred was because that reflected quite a particular worldview from the people who work at Google. Let me just jump in on that.
00:14:09
Speaker
That is the accusation. That is not a fact. You're getting the median internet answer, including all of the biases that are on the internet. And if you didn't control and train for that, that's what will come through. Now I agree, like show me the US founding fathers and you get a wonderfully multiracial image back. Sure.
00:14:37
Speaker
I understand it, but to leap two, that is inherently at the level of the people who wrote the algorithm versus that's at the level of the data that it's scraped is turning a valid area for exploration into a hard fact that we have not verified. There's another risk that pops up in this conversation, of course, and that is that the machines will take our jobs.
00:15:07
Speaker
Anand, how do you think about the threat to jobs and the risks of job losses and how should people be worried?
00:15:16
Speaker
So I'd say like, you know, AI is more of a mind shift change, right? So there will be certain jobs that are repetitive that I think AI can absolutely do. And those I think would go away. But you know, you'd look back with like 30, 40 years, right? So people said the same thing about computers. They said that when computers come, like, you know, a lot of jobs are going to go away, it's going to replace humans, things like that. It did. It actually helped because we could achieve a lot more. And I think of AI
00:15:43
Speaker
just that but like on steroids, right? Because I look at AI is now being able to do so much more kind of enhancing our scope and our capabilities to try and test, right? I'll give an example. So with AI, you can actually have like, you know, augmented reality on spaces where you can now test your strategies, right? Now, the way you think of it is you don't need to have specific market segments where you're trying to tracking it. AI can help you do that in this virtual environment with minimal risk.
00:16:13
Speaker
The way you think about it is going to be different because you don't need a super marketing strategy with this thing, that kind of thing. You're thinking about it very different. You could probably take more chances, things like that. So I don't think it's going to necessarily replace jobs the way this is not like a doomsday thing. I think what's going to happen is, though, as humans, we're going to have to rethink how we approach a solution to a problem.
00:16:37
Speaker
So think of it as you know what the outcome is. You can basically take a leverage AI to take you to a good level, but just knowing how to ask the right questions, where it can help you, where it can augment you. So then you are using its expertise to guide you down the paths to the answer that you're looking for. Okay, we've got the scary stuff out of the way. Let's focus on the opportunities. Rick, what are the business applications of AI that you are most excited about?
00:17:06
Speaker
Literally everything. The thing I'm most excited about right now is the world of generative AI, right? So if you break AI into two big categories, discriminative, I read patterns and I sort based on those patterns, and generative AI, I can create that which is new based off of data that I've been trained on.
00:17:30
Speaker
I think that's fascinating. And I don't think that we've even started really to scratch the surface on what we can do there, whether that's something that's internal facing, we can do what we do, but we can do it faster, better, cheaper, or we can now do things that we've never done before. And then where I think it gets really fun and we're certainly Ananda and I spend an awful lot of time.
00:17:52
Speaker
playing and guiding clients to play is what happens when you snap together. Generative AI, which is enormously powerful with say a predictive AI that falls into the discriminative camp and you put those two things together and then you put in a vision AI on top of it. So now it can also see. Then you really start creating some fascinating
00:18:19
Speaker
Capabilities that will not only lead to that, which you can envision right now, but things that we haven't yet thought of. If that knitted together capability exists, that composed solution, you can start having fun.
AI and Personalization: Benefits and Privacy Concerns
00:18:34
Speaker
One of the things that I say in addition to what Rick said is hyper-personalization, right? So imagine like today what happens is that when you look at a lot of the strategies right on personalization, you're fit within a cohort or a persona and the treatment options or the offers that you have is catered to that persona.
00:18:52
Speaker
And that's great and that works and we try to get deeper and deeper, but it's very difficult to get to that personal one. But with AI, what I can do is I can actually create a digital avatar of you to now simulate what you would like and what you wouldn't.
00:19:06
Speaker
And that now I can say, I know I can say with high confidence, Will's going to like this, Rick's going to like this and it's not going to like that. So don't give it to him. Right. And that hyper personalization is actually possible through the things like what Rick said with the composability, because now the way I snap these things together is actually is going to describe who you are. And I can actually test that out to the person of one literally.
00:19:32
Speaker
It hasn't become clear throughout this conversation so far. I am not an AI expert in the way that you two are. I want to understand the simulation process a bit better. What does that look like? How do you do it? Paint a picture for me.
00:19:45
Speaker
Sure, absolutely. I can take a stab, Rick. So the easiest way to think about it is, you know, when you think about generative AI, right? So one of the powers of generative AI is it can take the data that's available, you know, just say on planet earth. It takes the questions that you're asking and actually can generate new content.
00:20:02
Speaker
Typically what you're used to save the chat GPT as you ask questions like, you know, who is the founding fathers? How do I go from place here to place be things like that? Like you ask questions like that, but you can actually ask it to generate data. You can actually ask it to generate augmented spaces.
00:20:19
Speaker
And when you do that what happens is as you start getting more advanced you are now creating like almost simulations by saying if i feed in this kind of data with the person of this persona what would the reaction look like and if you think about it right that's if you kinda like merge the digital and the real world together like.
00:20:38
Speaker
A lot of marketing strategies, that's what they're doing, right? With their test population, they're taking the small market segment and they're saying, if I did this, what happens? If I did B, what happens? And that's the concept of A-B testing. But why test it on like real people when you can actually do it on the digital avatars, which is basically just like this augmented data to simulate the outcome to know what the response would be. And so, Will, if we extend that to like an example, think about the
00:21:08
Speaker
every retail site you now go to that suggests other things for you. And so I've been a heavy user of Amazon going back to when they just did books. And here are your recommended books. And I love Amazon. I am a fan. But like at least 70% of that list is like, I hate that author. I hate that author. I've read that book. I bought that book through you, right? And of course they've refined and they've improved over time.
00:21:37
Speaker
However, with generative AI, what Anand was referring to is like you can create something called synthetic data, right? So you can create those avatars. And when you start to move into places where what got personally identifiable information, I don't want to be shipping risk data all over the place. You can create what amounts to a virtual idea of me that will get more and more refined such that things like those recommendations are like, Oh yeah, I do want to read that book.
00:22:08
Speaker
Oh yeah, I do need that pair of shoes. Or oh yeah, I do need that financial product. Or oh yeah, my body would respond a particular way to a new mechanism of action that a life sciences company is using to create a new cancer drug. It's extraordinarily powerful. It protects privacy and it allows you to run simulations, not on a population, but on a person.
00:22:38
Speaker
That is extraordinarily powerful. There's a lot of cool stuff being done with that. And it's new, man. Whatever we're doing right now in 18 months, what we're doing with it is going to be so far beyond where we are now. It's so cool. There's so many things you can do when you just start thinking, hey, create this new data for me. It's not that easy, right? But it's pretty close to that easy.
00:23:07
Speaker
Very exciting. I think customer experience and digital nerds have been talking about hyper personalization for years and years. And this may finally be the magic that can get us to that point. Rick, I want to go back to the combination of generative and predictive AI.
00:23:24
Speaker
When you were talking about that, my mind went to customer engagement and customer servicing. So I speak to a lot of clients at the moment about digital channel shift. How can we get more customers or patients engaging with us via digital and unassisted channels like chatbots? Is AI a license to do away with human engagement and human interaction as part of your servicing strategy, or is there still a place for people in the future?
AI's Role in Enhancing Human Interaction and Operational Efficiency
00:23:53
Speaker
Oh yeah. You think about what we're so enamored with with generative AI, right? We've been doing it as humans for the entire time that we have populated the earth. What generative AI will allow us to do is to be able to better predict, prescribe, create for folks. But while there could be a dystopian future,
00:24:20
Speaker
where the machine has taken over and there is no longer a place for us, that dystopian future has been predicted fairly regularly in 20 to 30 year cycles going back to the advent of the cotton gin. At some point in time, it could be right. It just hasn't been yet. And I think Anand's answer back at the beginning around, no, it will change things.
00:24:49
Speaker
It will absolutely change things, but we are humans living in, living amongst each other. At some point in time, you're going to interact with another human and you're not going to have AI there to tell you what to do. And it may or may not be in a business context, but we're still going to be here.
00:25:13
Speaker
We're still going to be the dominant species. And if the machines eventually win, I can't wait to live through that movie. It'll be fascinating. I'm just not making any bets on it happen at any time. I can see you as the Terminator, Rick. We've been talking front office, hyper-personalization, growth, customer understanding, much the same with customer engagement. Go to the back office, operations, efficiency. Does AI have a role to play in making your business more efficient?
00:25:42
Speaker
Yeah, absolutely. And I'd say there are companies that are already doing that. So Lowe's is an example. One of the things that they do is they have robotic arms to help stack heavy lumber or heavy goods in places that are more dangerous, sort of like hard to reach places.
00:25:57
Speaker
Where AI can help you is that, you know, this kind of comes back to that original question you asked about, is it going to replace humans, right? You look at AI as being the tool that's going to help you do the tougher tasks, right? And I think that's the mindset that you put.
00:26:13
Speaker
And when you do that, there is a lot of back office that say smaller things like check recognition. These are things that actually happen today. You want to deposit a check, a physical check. You don't have to go to the bank to do it anymore. You can use your phone. What happens? AI reads the check, it translates what it is, make sure it's authentic, and then it actually does the deposit that's been there.
00:26:36
Speaker
And that's how I'm thinking, how I think it'll start transforming a lot of our back end, right? AI is going to take a lot of these repetitive tasks that, you know, you don't need a human to do because, yeah, I can do it. I can do it better. I can do it with less errors. And where the human comes in is now trying to figure out how to leverage a lot of these tools to make these processes better.
00:26:57
Speaker
That's how I look at it. So when you think about call centers as an example, right? Where AI, it's already being used right now and will start getting more proliferate more is leveraging a lot of like generative AI in helping the call center agents answer questions, right? So the number of escalations is lower. So what does that mean for you? If the escalations are lower, you're getting your questions answered faster without an agent telling
00:27:22
Speaker
I don't know let me escalate it to a manager and then waiting for the manager to join. So those are simple things but it can get much more sophisticated than that. Let's return to the question that we flirted with at the outset, which is, well, as a business leader, what do I actually do?
Building AI Literacy and Strategic Alignment for Leaders
00:27:38
Speaker
If you're a CEO, heard obviously that AI is important. You want to start thinking about how do I put an AI strategy in place and then execute upon it. Rick, where do they start? What should they be thinking about?
00:27:52
Speaker
The very first thing that I would do would be to try to get my leadership layer just a basic understanding of what AI is.
00:28:02
Speaker
and how it works, that is a significant impediment right now, in that either we see folks at that level who are like, it is going to change everything, I no longer need employees, and I will be 20 years younger and cooler. It's none of those. Or on the other end, because of the risks, and the risks are real. I'm not trying to say that they're trivial, but because of the risks like, no, don't touch it, don't do it. The actual truth is in between.
00:28:32
Speaker
And so until we have the folks that ultimately make these control the decisions for the organization and control the budgets, it doesn't matter how many great ideas your, uh, more junior folks are churning out and trust me, they're churning out great ideas until there is some measure of basic AI literacy. And we're not talking about fluency.
00:28:58
Speaker
We're not even talking about being hugely conversant, but just an understanding of it. You got these two big chunks, generative and discriminative, and then you can take different things and snap them together and create things of more value. Until the executive layer gets really comfortable at that, we're going to see more of what we've been seeing, which is companies essentially playing whack-a-mole with AI.
00:29:23
Speaker
where those folks that are empowered up to a point to do like, well, I can do a project like this. And it's really cool. And somebody else is doing a project to address something else. And it's really cool. And et cetera, et cetera, et cetera. We won't have a unified strategic view of what we as a company need to do. If you solve that, and again, we work with clients on exactly that, you see them start to open up.
00:29:48
Speaker
and get much more strategic and much more effective and much more programmatic about AI versus a lot of project based stuff that by itself doesn't do that much and doesn't really expand very much. And I'll go to the other end of the corporate ladder.
00:30:08
Speaker
I know several younger people who listen to our podcast, people who are starting out in their career at the moment are facing a future where their career will be very heavily influenced by AI. What advice would you give to someone just starting out their career to navigate an AI future?
Encouragement for Young Professionals: Think Big with AI
00:30:27
Speaker
Sure, absolutely. So I'd say, you know, think big, dream big, know what you're trying to solve and know that there is probably some AI that's there that's going to help you solve it. There are AIs that help you understand other AIs. So, you know, you have a plethora of information and tools available, right? The issue is not a lack of resources. The issue is the lack of thought leadership or like that vision, right? So if you can envision in your mind what you want to solve,
00:30:56
Speaker
you would be surprised that you could string a set of tools like with AI that it can actually solve it. And I'd say that's going to be your biggest differentiator as you're working in the corporate space, right? It's not going to be your prowess in how you are coding. It's not your prowess in being able to do like the niche analytics, things like that, right? It's your ability to think from a very product-like perspective and say that
00:31:21
Speaker
I want to deliver this experience to solve this problem. And so to do that, that's the solution that I need. And once you if you can master that, then you are now in the spot where you just have to research like what are the different AI tools that composability that Rick was talking about? How do I string it together? Because that's going to be a big differentiator.
00:31:44
Speaker
It's a lovely sentiment to end on. There are some eternal truths in business. It doesn't matter what new technology comes about. Focus on the customer and then work back from there will always hold true. Gentlemen, we have the link to both of your contact details in the show notes. If anyone wants to reach out to chat, it's a very exciting future that we are looking towards. Rick, Anand, thank you very much for coming on, speaking from experience. Thank you for having us.
00:32:13
Speaker
Thank you very much for listening to this episode of Speaking from Experience. If you enjoyed the show, please leave us a rating and a review. And if you really enjoyed the show, reach out to us for a chat. A link is in the show notes.