BizTech Forward: Why 'AI-Ready' Companies Aren't Actually Ready

Anni Tabagua: Hi everyone, welcome back to BizTech Forward. In the next couple of episodes, I'd like us to focus on AI. I know, shocking, but it's all we hear these days. Wherever you look, you see companies claiming they're AI-first or transforming with AI. I'd really like to understand what is hype, what is real, and what is actually happening.

To discuss all this, I'm joined by Alistair Wandesforde, a senior executive at DataArt, who leads and supports large-scale digital transformation across various sectors, including finance, travel, healthcare, and education. Furthermore, he also leads DataArt's Program Lab and manages colleague communications for the Global Account EMEA organization. Alistair, thank you so much for being here. I'm really excited to have you on the show.

Alistair Wandesforde: Thanks. It's a pleasure to be here.

Anni Tabagua: Let's talk about what's really going on with AI. Hopefully, we'll talk about the messy reality and things you don't really hear that often, and where the actual opportunities are these days. Alistair, you have so much experience, more than 25 years in the business. I bet you're having a lot of customer communications, and you watch everybody, afraid not to add AI to their pitch. Generally, when you walk into a room and you hear somebody say "we are AI-ready," what do you actually see?

Alistair Wandesforde: It's a great question. And I should be clear as we frame up the conversation. The area of this entire AI experience that I am particularly interested in is where it intersects with people. I'm not an engineer first. I was going to say ‘people-first,’ but that's our motto, and it sounds a little corny. But I'm very interested in the intersection of new technologies, or technologies in general, and people. That'll be the context I can provide best for this conversation.

When I walk into an organization, and somebody or the group tells us that they're ready, the answer is maybe. There are a lot of dimensions. I think many people would say no, you're not ready. Or someone might also say, 'Of course, you're ready.’ But for me, it's much more nuanced than that.

I measure readiness not only in terms of are you actually ready, because my first thought is, well, do you have the data? Do you have the systems? Do you have a business problem that you're trying to solve? Those things are all true. Very often, it's the case that they aren't ready, because how can you be ready for something that just showed up yesterday, when you already need to be operating tomorrow?

But more importantly than that, I think the thing that people aren't ready for, and I don't think any of us can really be ready for, is the amount of change that they're about to go through. The readiness isn't just the technical readiness and the systems readiness, or even having a problem that you're trying to solve. It's the impact of enabling or using these technologies, such as AI, and the actual change that occurs within your business as a result. Not just in terms of how you respond to emails or communicate with people, but how does your business actually evolve? I don't think anybody's ever ready for that level of change when something like AI comes along, or generative AI, maybe in particular.

Anni Tabagua: But do you think it's radically different from previous tech waves or something that happened before?

Alistair Wandesforde: I don't think so. I mean, I was around when my first TV was a black-and-white set, and rotary phones and newspapers arrived daily to share the news. I've witnessed a significant amount of technological change over the last 40-plus years. People way smarter than me have documented the hype cycle and the way technology arrives. I think this isn't for me any differently than any other technology wave or technology that has emerged. I think that it has characteristics that are definitely different. I think there's an urgency to it. There's a pervasiveness of it. I think it is a very different kind of technology, but I'm not sure. At the end of the day, for me, it's just another technology.

Part of the way I measure that is that it has already changed three, four, or five times since it first appeared two years ago. What it was when it arrived, versus what it was 18 months ago, versus what it is today, is changing very rapidly. And again, technology, new technology in particular, that's meeting the market for the first time or out in the world for the first time, is going to change a lot.

It's more a question of speed, the rate of change, and then the impact that it starts to make on people, if that makes sense. So, I think fundamentally, no, it's not any different in terms of how it's manifesting and how we're experiencing it. Yeah, it's happening very quickly and very dramatically.

Anni Tabagua: I'm so glad you mentioned the people aspect, and that the entire conversation is going to be framed around people, because I often find myself thinking about people. I keep reading the news and the headlines. As a person who keeps up with the media, I've noticed that all the headlines these days consistently claim that AI is already replacing consultants, major consulting companies, and vendors. You are next. You will not be needed anywhere. Nobody needs implementation partners. But what is actually happening on the ground? I keep wondering. It may sound a bit naive, but with all these unprecedented AI transformations, don't companies need more help, not less?

Alistair Wandesforde: 100%. Companies and their people, the individuals who are the very fabric of those companies, need a lot of help. People aren't going anywhere, as far as I'm concerned, in the near term, and I think even in the long term. What people need help with is what's happening. What are these tools? How are they impacting my life?

I think the headlines are jobs will be eliminated, but for me, there's a way to look at that and say that's just a role or a title. The nature of conducting business or running a business is unlikely to change fundamentally. If you're selling donuts, software, or financial services, or if you're a healthcare company, you still have to provide those fundamental services to your customers. Importantly, in the near term, AI is not going to allow you to do brain surgery at scale across the globe, suddenly. Sure, are some people going to be new AI surgeons? Of course, but there's going to be a lot of demand and need for people to do traditional brain surgery going forward. I think the same is true of most jobs.

Now, the threat and the reality are that the tooling with which you do your job, and the way in which you do some of your job, are being pushed and almost forced to adapt much more rapidly than we've had to adapt to change in the past. If you think about the fax machine, text messaging, or even email, these are things that took quite a while, even when they were revolutionary or advanced, to really spread and change the way work was done. There was a long time before legal documents could be signed electronically, for example, when the capability had been there for quite some time.

So, I think the way that I think about it is that we need to help the people. In this case, the people range from business users to developers, who are actually evolving the way they work to help them learn as quickly as possible. Because some of these tools are very impressive and can really improve the way you communicate, operate, or improve efficiency, or at least we're told that. And at the same time, understand how what you're doing may or may not change as a result of that technology that you've now incorporated into your work. Customer service remains customer service at its core, whether it's a person-to-person interaction or a company-to-consumer relationship. The importance of how you handle that communication won't change. The way you conduct that communication, of course, may change significantly with technologies like generative AI and chatbots.

Anni Tabagua: So, the answer is education, education, and more education. Familiarize yourself with all the tools, learn, and stay up to date instead of worrying.

Alistair Wandesforde: Yes. And a lot of therapy. I think we all have to be therapists to one another and help each other work through it. I mean, education for sure, but I think helping people work through, maybe not therapy exactly, but certainly working through what the nature of these tools allows us to do, is a lot of the work that we have to do. I think we're already seeing this in our customers, and in the types of work we're doing, as well as in the way people are asking for help.

Anni Tabagua: Over this past year, did you notice anything that seemed surprising to you with AI and people and customer conversations, something that companies struggle with that you didn't expect?

Alistair Wandesforde: That's a great question. Honestly, a lot of the struggles are immediate and obvious. I think the one aspect of this change that I'm seeing increasingly is the tension, or the relaxing of tension, around the timescale. The most difficult thing to wrap your head around is how quickly things are supposed to happen in an environment like this.

There was a need when this arrived, which I can describe in broad terms, and I never really know how to frame it because it's so much more, I think, than just chatbots or generative AI. However, I think that because it was so accessible, you needed to incorporate it successfully by tomorrow. Somebody showed it to you today. It needs to happen tomorrow. And I think the thing that is happening is that it really takes time for this to occur. And I think that is why people are now recognizing that we won't change overnight. The inertia of life does not actually allow you to go from zero to 100 and be effective at 100.

I think I was surprised by how quickly people really thought successful change would occur. What I'm seeing now is, of course, that that's just not how life works. Even having a baby, you're pregnant for nine months, you're excited. There's all the buildup, the baby arrives, and there's the newness of the baby. But pretty quickly after that, you still have the life that you had before. But now you have a baby, and you're nurturing, growing, and caring for that baby. And it ultimately becomes a lifelong journey. You get that same moment where I didn't have it one day, but I have it the next day. It's life-changing. Everything's going to be different. But then a lot of it's the same, except you have a baby and now you have to take care of the baby. And then that, of course, alters your life forever. You become a parent. Eventually, maybe a grandparent. All those things that happen.

Anni Tabagua: This is brilliant, the analogy. Having a baby. You painted a really clear picture. This will stay with me.

Alistair Wandesforde: But I happen to think a lot of the software development lifecycle and the work that we do is a lot like life, but that's maybe a conversation for a whole other podcast.

Anni Tabagua: From your experience, also thinking about the human side of things, when you witnessed an AI project fail or fizzle out, what is usually the reason? Is that also the timescale, and are people so impatient to achieve successful results?

Alistair Wandesforde: A little bit. That would be a quick ‘yes,’ I think. But the way that I would think about it is that, again, people don't understand how much effort it takes, actually, to change the way you do something. I see things failing now because it was either a little bit harder to do, and they sort of lost focus, or they took on a problem that was too big. Or they may not have been ready in some underlying way. So, you just couldn't make the steps to get there. It's the old "if you have bad data in, you're going to get bad data out." A lot of this stuff that you want to experiment with, if you don't set that experiment up in a proper way, then it's basically bound to fail before you start, for any number of the reasons that I just described.

I'm not surprised by any of the failures that I see. I'm much more interested in what we can learn as a part of that process, and have we created an environment for the next experiment? Have we ever? Do we have something that we can take away from what we just experienced and move forward with?

I'm a little surprised when people throw up their hands and feel like they've hit a wall or reached a stopping point, when in fact it should be like we always talk about: fail fast, work iteratively. There are plenty of statistics that prove something like 95% of whatever's out there hasn't made it to production, and people are still trying to figure out where their returns are. That's evidence to me of just a very fast early cycle. And the next cycle is going to be even more productive. I see that in the conversations that we're beginning to have. The big spends, the big investments, the leaning in has happened. Everybody's cranked themselves through it one time. And if they've made some progress, they can maybe make some measurements.

But really, what I think I'm seeing now is that people are trying to put themselves into, well, where do we really want to be based on what we've learned a year from now? I think that the time horizon has changed, and I think that's the biggest outcome that we've all got collectively from this first chaotic early cycle.

Anni Tabagua: Absolutely. Another thing I wanted to ask you is that I keep reading some preliminary reports for next year, which include a lot of advice to CTOs and similar information. I see that many experts keep saying the same thing: stop chasing the best AI model. Please think about the fundamentals.

And I wanted to ask you, we discussed previous tech waves and how AI is not that different, but it somehow feels like this time, the fundamentals don't apply anymore. Did everybody just forget about the importance of the basics all of a sudden? Do you think it's true at all?

Alistair Wandesforde: I think everybody forgot about the basics. I mean, that's how I was. I think everybody did. I think everybody thought that this technology was going to change everything. And everybody very rapidly put all their eggs in one basket and thought that things would be different on the other side.

Now, I'm obviously being a little bit dramatic, but I'm saying it that way because I absolutely believe that if you didn't start with first principles, you now need to return to first principles. Begin by saying, well, what is it that my business does? How can I apply this technology to what I do for the most successful outcome that I can possibly achieve?

Now, again, the thing that's different about this technology, or I guess the thing that's different, is the scale at which this applies. If you think about new music formats, such as transitioning from videotape to DVDs to streaming, that has affected everybody. But from a business perspective, it was a fairly narrow and channel-type experience. It impacted everybody in the chain. But it wasn't like everybody all at once. Consumers had to wait for certain things to evolve in order to reach specific milestones. And then, all of a sudden, I stopped watching VHS tapes. I was just streaming everything on Netflix with DVDs in between.

I think to go back to first principles, you have to say, where is my business today? What is it that I'm trying to accomplish? How can I apply this new technology to those problems? The new dimension is that everybody is applying it to all of their problems simultaneously, which introduces a higher risk of existential threat to your own business model from competitors or startups. So, you might have a business model today that was somewhat insulated previously due to your technological advantage. You had more data, better systems, a customer base, or something that gave you a bit of a differentiator or a cutting edge. I do think that this particular technology evolution or revolution is pulling down the barriers to competition in a much faster way.

Again, that said, just because I come up with a competing business model to an institution that has existed for 100 years doesn't mean that its 27 million customers are suddenly going to become my customers. So, no matter how quickly this stuff evolves, it goes back to what I was saying at the beginning, which is that people don't change that quickly. They just can't. Parts of them can. But as with the baby analogy, you're not a different person after that baby arrives. You become a different person going forward. And so that's the change that I think we don't fully... It's boring, honestly, if you think about it. It moves too slowly. Nobody wants that headline. But for me, the people part of it, that's the part where the work continues. The challenges will remain.

To go back to what you were saying earlier, that's what we're here to help people with. And so, I think what we've been doing to help people from the beginning of DataArt's existence is how to navigate the constantly evolving landscape of change in your business and use technology to enable solutions for where you're trying to get to, the outcomes you're trying to achieve.

Anni Tabagua: Alistair, culturally, when you see companies that succeed these days, I'm not talking about the tech stack. What is it that, what is it that they all have in common? The ones that succeed culturally, structurally, people-wise? What is it that they have?

Alistair Wandesforde: They have really smart people who collaborate well together. So, they have people who enjoy working on the problems that they're trying to solve. They have people who know how to work together to solve those problems. They have experience solving those problems, or they possess the energy and enthusiasm to tackle a problem they've never encountered before.

The culture is one of openness in terms of communication, as well as in questioning what we're doing and how we might do it differently. And then fairly quickly, they have processes. I mean, that's a boring word, but they have ways of working that support that culture. Those are practiced. They've been there before. It's that sense of knowing how to work together or with our partners to solve whatever challenge comes at us.

You can take any challenge you had before AI that you were trying to solve with technology. It's the same challenge now. You're using a different toolset so that you might operate a little differently, think a little differently, have different solutions. But I think the organizations that will succeed, that are succeeding, are the ones that had that problem-solving capability and that culture of support and the ability to fail-safe built into them from the start.

Anni Tabagua: The more you talk, the more I can see how all that translates to real life. What is it that makes you succeed? It's communication, being open and questioning things with your partner, with your friends, family, and at work. It's very interesting to see how relatable that is to anyone, not just developers.

Alistair Wandesforde: Yeah. And everybody's going to need that. So, the thing that is happening right now for sure is that everybody feels threatened. I feel threatened. Will consultants, advisors, or knowledgeable individuals be needed, or will people simply tap into an engine and retrieve information? And the answer is yes. People will continue to do all of that in the future. And how I communicate with people and how I communicate with my teams will evolve and change. But at the end of the day, we're still going to be people trying to figure out how to solve problems. And instead of stones and flint trying to start a fire, we're going to be trying to figure out how technology, this new technology, is going to help us solve different kinds of problems. Not just looking at, but also considering the future of humanity and not having our planet burned to the ground around us.

Anni Tabagua: I really want to ask you a question that just came to mind. We might edit it out. I'm not sure, but I'm very curious. When I read the media, headlines, and comments to stay up-to-date, I see a lot of people reacting to AI conversations with a huge eye roll, saying, ‘Enough already, guys, stop it.’ We cannot. We get it, okay? We get it. And I wanted to ask you, Alistair, is it still important to have these conversations, or is it just, 'Okay, whatever’? And if it is important, why is it important to talk about AI?

Alistair Wandesforde: It's absolutely important. I think the AI eye rolling, I mean, I don't know why the AI eye rolling comes. Everybody's going to roll their eyes at some point. But I would take away from AI eye rolling at this point in a certain way. It's saying we're done with a certain type of conversation. However, you can't escape what's happening fundamentally. That's crazy. I think we can move on from or be tired of certain conversations that we've been having for the last six months or the last six minutes. However, this conversation will never end. I mean, this isn't something that just goes away.

You could even pick a previous technology that certain aspects of the world became very excited about, such as blockchain. It became fairly boring fairly quickly for people, but honestly, it still exists and underpins a significant amount of global change in technology services, perhaps not as broadly as AI, but it's still out there. It's still going strong as an idea, a concept. The tools, the implementations, and the way it works are all different. The same will happen for AI. So, the conversation can't end. I mean, that's crazy. What are you not talking about? What is actually happening in the world? For me, that would be insane. I think the way we have conversations and the topics we're discussing are already changing.

I think I could get on board, probably, with some of the comments if what we're talking about is yet another conversation about how amazing something is and what it can do for you, or the way it can be implemented. That's super boring. What I'm interested in is how we can apply what we've learned to the problem I have today to make a change in my business tomorrow. And that's an eternal conversation. That's evergreen. That's always going to happen.

Anni Tabagua: I'm glad I asked. And say if I were, I don't know, a CTO of a large company and I've been building software the traditional way for ages, but now I'm under pressure to do something with AI, but I cannot afford to mess up what we already have. So, what's the conversation I should be having internally, for instance, before talking to a vendor?

Alistair Wandesforde: Yeah. I mean, I think this goes back to when you asked, ‘Are people ready?’ I mean, I think one of the things that is difficult to get ready for is a clear statement of what your problems are.

So, even before you address things like whether your data is ready, which is, of course, the important technical problem to have ready, you need to understand what your problems are.

If there's somebody out there who's been working in their traditional ways, and we have some customers who are like this, and they may even be a little bit AI-aware and forward, and maybe even think they understand it, or let's say that they don't really understand it at all, a more extreme case.

However, they're under pressure from their board or leadership to do something with AI, as you mentioned. The place I would hope we start, a place I would personally start, is with a conversation about the problems you face today in your business. Not in your technology, not in your data, not in any of those things. But what is a business problem that you're trying to solve?

Technology is basically behind everything. Every business problem or every business solution. So, what's the problem you're facing, and how can we break it down into a manageable piece that we can take a step forward with? That we can make an experiment. And you can decide how meaningful you need that experiment to be. Perhaps you're at a critical juncture where you need to make a significant impact. Or maybe you're at a point where you can take a step forward and bring back some information, data, or results to continue the conversation.

But if you haven't anchored yourself in a problem, there's very little, in my experience, way to move forward in a meaningful manner, because what you end up doing is spending your time talking about the tool, the shiny object. Some information on what that is. And it never transcends the abstraction of technology into something that someone else can understand. The business doesn't understand tools. The business doesn't understand story points or the five defects that are less than you had the month before. I mean, they might have some idea of it, but it doesn't mean anything to them. It's not like we generated another million dollars in sales or acquired 25,000 new customers, which is the language they would want to hear.

So, I would want to start with somebody who's facing this predicament, and what's the real problem you need to solve? And then let's figure out how we can utilize AI or any technology, specifically AI in this case, to help you design an experiment to solve that problem.

Anni Tabagua: I really appreciate your common-sense approach and your directness. It's very clear. I could keep asking you questions for another day. But as I wrap up, I always like to ask our guests if they have any unpopular opinions on the topic. So, is there a hot take you could offer us?

Alistair Wandesforde: A hot take? Well, I'm not known for my hot takes, but I think that maybe my hot take is that I don't think AI is as scary or as revolutionary as everybody out there would have you believe. I think that it is evolutionary. I think that it will, of course, fundamentally change a lot of things in our society. It has already disrupted technology and our perspective on it.

However, if you examine what it will actually require in terms of infrastructure, namely building data centers and providing sufficient power to support all the tasks that people claim to be able to do or want to do with AI, we're already encountering a massive amount of inertia. And so, I'm not sure if this is a hot take or not, but I just don't think things will actually change as rapidly and therefore not as dramatically as everybody thinks they will. I think we will receive increasingly smaller amounts of change as we move forward.

And on top of that, there will be a lid pushing down on the literal physical constraints, both in terms of human consumption of this technology and the infrastructure and support required to enable it as we move forward. So, another way to say that is I don't think this is going to be as dramatic as everybody makes it out to be.

Anni Tabagua: Thank God. That's kind of refreshing to hear, actually. And just to end on a future-looking note, what do you think about next year? I'm going to combine these two questions I have in my head because I wanted to ask you, hey, what do you think about 2026? What should we all be watching most closely? And another thing I wanted to ask, Alistair, what is it that you are most excited about in this area? Not necessarily for work, but generally in this area.

Alistair Wandesforde: So, the thing that I actually got the most excited about when it got to a certain point, other than just being fascinated by how amazing the technology was, was that I got most excited about was, so I'm not an engineer. I'm not sure I've ever written any lines of code other than when I was in grade school, possibly using BASIC, and taught a turtle how to make turns on a screen. I just never could sit in front of a screen long enough and type.

So, the thing that I actually got the most excited about recently was actually learning how to become a developer. And so the thing that I have been experimenting with personally is how to, I mean, I guess it's a version of vibe coding, but basically, how can I take a problem or idea that I have and use these tools that everybody says allows everybody to do everything so quickly and literally turn an idea in my head into a working application, a mobile app or a website or whatever.

And so, for me personally, that's been the most exciting, because it's allowed me to take something that, I mean, I guess arguably I know a lot about what it is to be a developer, but as I'm saying, I've literally never developed code in my life and tried to teach myself how to do that. Not how to be a programmer. Not how to write the lines of code, because AI does all that for me. So, what I'm actually doing is taking my problem, which is that I want to create a memory box where I can search for everything I've ever done in my entire life. And you can start typing in those ideas into any number of the tools that have evolved and start getting back code, user interface, how to do the data, all of the different things that you would do.

And then I can work through it again, just in my own language, plain English, to see what it is I want to accomplish and watch it come to life. However, because I'm actually developing the software, I have to go in and try to understand what those problems are. So, again, maybe it's not actually teaching me to be a developer, but it has allowed me to take ideas that I've had in my head and develop them on my own, as opposed to needing a developer.

Now, what I've learned in all of that is that I, by not being a developer, actually fairly quickly, I have no idea what I'm doing and desperately want a developer to be sitting next to me to be helping me figure out what it is I'm doing and how it is I need to address the problems that I'm seeing. So, in some ways, it's actually validating what we discussed earlier, which is that people will be essential throughout this entire process. I can't actually do that as of today; I need to develop something on my own. At a certain point, I want to be able to turn to someone and say, ‘Hey, how do we solve this problem?’ What is the problem I'm seeing here? How do we help move this forward?

And so, for me, that's at least in my own world, a perfect example of what the technology is enabling, yet how the human element will remain for basically forever. I don't see that changing anytime soon.

Anni Tabagua: I'm really happy to hear that. When you mentioned that at some point you realized you needed actual help from a developer, I would say from a human developer. It's not a human developer. That's refreshing to hear, indeed. Alistair, thank you so much for this conversation. I really enjoyed it. I think we need more direct and honest conversations like this. So, thank you so much for taking the time.

Alistair Wandesforde: Thank you, and thank you for your time. It was a pleasure to speak. I really appreciate it.

Anni Tabagua: And to our listeners, thank you for tuning in. If you have any thoughts on this or disagree completely with something we said, please let us know at biztechforward@dataart.com. But that's all for now, and we'll see you next time.