Disclaimer: The Futurum Tech Webcast is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded, and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors, and we ask that you do not treat us as such.

Transcript:

Daniel Newman: Hey, everyone. Welcome to another episode of the Futurum Tech podcast. I’m Daniel Newman, your host, CEO of The Futurum Group. I’m excited for this interview series we have today. We’re going to be looking at future forward IT. We’re going to be making predictions about the future of IT, talking about AI powered analytics and so much more. And we’ve got Trevor Schulze joining the show. Trevor, first time guest. Thanks so much for joining.

Trevor Schulze: Hey man, thanks for having me. I’m looking forward to this.

Daniel Newman: Yeah, it’s great to have you here. You immediately became my friend when I saw that McLaren hat behind you. Big Lando Norris fan here in my house. Anyone that’s followed my Twitter stream will actually see me and my son in our papaya gear.

Trevor Schulze: I love it.

Daniel Newman: Each and every Sunday during the race season, what do they say, they do 23 or 24 Super Bowls a year? It’s every week or other week. So I know Alteryx is a sponsor of McLaren, but hopefully you like them as much as I do. But I digress. Not the topic of the day. We’re going to talk a little bit about AI powered analytics and so much more. First and foremost, Trevor, why don’t you just do a quick introduction since this is the first time you’re here on the show. Tell us a little bit about yourself and the work you’re doing and your journey at Alteryx.

Trevor Schulze: Yeah, hey, and again, thanks for having me. I’ve been in high tech for over 30 years now, and I have to say probably being a CIO for a high tech company is one of the greatest jobs in the world, especially at Alteryx. And the big reason is I have a front row seat at the center of a really hot and critical market, as you said, data analytics, AI. I get to see the products being built, I get to hear about the inside scoops, and I also get to talk to customers, and that’s the two sides of my job. My CIO day job is to, like most CIOs, help grow and enable companies, and in our case, we’re scaling up to be a multi-billion dollar company. And as you can imagine, being the CIO of a high tech company, the expectations are super high on how we operate, how we perform. Everyone in my company is an expert in IT. So we as an IT group need to model that enterprise of the future. I’m proud to say that we’re the company that’s a hundred percent in the cloud. We’ve got multi-cloud workloads, scaled agile, data-driven enterprise, all the buzzwords that I’m sure you’re interviewing people on. And so it’s a really cool job to have, to be in this environment. And the other side, to your point about the evolving landscape, my favorite part of the job is I get to meet IT leaders all the time, hear about their challenges, their big ideas, and most importantly, as the CIO of Alteryx, learning and teaching and discussing what are the best practices and lessons learned around data and analytics and now AI. So it’s a very cool job and I’m very grateful.

Daniel Newman: Yeah, AI is definitely changing the landscape. I was at an event just recently for AMD, which is a little different business than you’re in, but obviously Silicon, I always say eats the world because you can’t run the software on air, you’ve got to have something to run it all on. But she got on stage and kind of said something along the lines of like she’d never in her life seen technology move as fast as it’s moved in the last 12 months. And I don’t think that’s an insanely unique viewpoint, but what it is, is it’s become really evident if you’re in this space and if you’re in a role like yours that the requirements to run IT for a large fast-growing enterprise in any industry, your disruption period, the amount of time you have to identify, decide, implement, and then kind of that agility to keep things going and updated, it’s endless. There’s no, okay, we’ve got the newest instance of Oracle, SAP, Salesforce updates, and okay, we can take a break. It’s like they’re going to add something tomorrow and you’re going to need to be on top of that. I mean, you must be literally end-to-end, wall-to-wall, every single day you and your org just making sure that you’re keeping up with A, what you have, and B, what you should have.

Trevor Schulze: Yeah, yeah. And hey, fun fact, I ran a large portion of IT at AMD a number of years ago, and semiconductor is my love. I was the CIO of Micron for a long time. So it’s having seen the different aspects of the industry. When I was at Cisco was the OEM side of the house, semiconductor with AMD and Broadcom and Micron, and now I’m in software sales and SaaS. And it is a discipline in our role, to have that growth mindset, to constantly be learning, to keeping up with the industry trends. And it’s the burden and the blessing of this job because people look to the CIO to be that person who can broker what’s going on. What are those new things that are going to impact our business? What the heck is this AI thing that I’m suddenly having to deal with? And as an engineer at my core background, it’s one of the things I love about this job, is the constant change and trying to use it as a competitive advantage for my company, whatever it is, that disruption that’s coming at us.

Daniel Newman: Yeah, no, I appreciate that input. And by the way, always funny how this world brings us back together. You probably saw or maybe witnessed from afar, there was a pretty big moment on the AI side yesterday, a lot of advancements in the chip space. But let’s talk about the shifting role. You guys had some really interesting data. Our intelligence at Futurum, as well, is really tracking a lot of these changes. We’re seeing some similar things. But it’s great, I talk so often to your peers that are the marketing product people, not so much. I actually talked to one of your peers, Adam Wilson, just the other day at Alteryx, but I love getting into your head because you’re kind of the guy that us as analysts are trying to influence, that you’re looking at the analyst, you might be reading something that we would write or something one of our peer firms would write, and that’s a part of the equation. How does that decision making change? Because I have to imagine it’s not just phone calls with analysts. What are you watching? What is the kind of zero to a hundred in terms of when you’re buying technology, how do you get started? What’s that first thing that kind of gets you to say, oh, I’m going to look at this LLM, or I’m going to look at this analytics platform, or I’m going to look at this hardware stack, versus then what’s the things that are kind of later on, Trevor, driving you to say, yes, this is the right one?

Trevor Schulze: Yeah, let me tackle all those questions-

Daniel Newman: Three, maybe five questions. So go at it any way you want.

Trevor Schulze: Let me see how I do, and let’s circle around if I missed any. I think it goes without saying, artificial intelligence is the most significant paradigm shift that we’ve seen in decades, if not ever. I mean, I was around NIT and product when the internet, I was at Cisco, we helped build the internet. I was a part of that. The mobile shift, the cloud shift. AI I think is catching everyone’s imagination. And I think the generative AI piece, that one branch, natural language processing, that visual computing, those branches of AI are now in front of everyone. And the numbers don’t lie. I mean, this last year was just crazy. ChatGPT everyone’s been talking about, right? I think it’s like 180 odd active users right now and billions of hits on a monthly basis. And everyone’s talking about it. And I am sure every podcast or every video, someone has an opinion. And when I think of AI, and I’ve been a discipline of AI for a long time, especially in semiconductor. We were doing machine learning long before others were. It’s a massive productivity. And it is now the central component, it should be, of everyone’s digital transformation strategy. It’s reshaping how organizations approach problem solving, decision making, and innovation. And now we’ve been discussing the CIO’s role in its emergence as the central and critical business leader for a long time. And these two things mashed together is a moment for IT professionals like myself, where people are now coming to us and saying, how and what are we doing about this? And so to your question about how I’m thinking about AI and how I’m making decisions and how I’m researching, it’s probably important to know who I am and which camp I sit in because I’m an AI optimist, and you’ve got people who are-

Daniel Newman: Me too.

Trevor Schulze: Yeah. It’s like you have the optimist and you have the catastropharians out there. And it’s probably a little bit of both, but I’m an optimist and I think we’re going to see AI quickly become a part of every digital capability out there because the potential is huge. And I think you probably have already covered this, so I don’t need to talk about the step function in human capabilities that we’re going to see this augmentation. And so I think from a decision making process, to your question, it’s really nuanced and challenging. And this last year, I think a lot of people have woken up and now they want to be a part of it. I not only get to sit and talk to our customers about how they’re thinking about it, but I also have to think about how I bring AI and these new disruptions into the company. And it’s a team sport. You have to have your legal team involved, you have to have your HR people involved. It’s really challenging because the decision making process really goes to the core of a company’s principles and ethics and what they’re willing to do with this technology and capabilities. But the reality is, every vendor out there is going to be adding an AI skew. Every startup you talk to is an AI startup now, and I hope that calms down because really it’s just people look at these new capabilities and say, this is the new way of doing X, Y, or Z. And so I’m advocating hard for every functional area in my company to think about human augmentation. What is that co-pilot, as some people say? What is that capability that’s going to make someone 10X what they do today? Because that’s what your competition is going to be doing.

Daniel Newman: Yeah. So I think that you said a couple things that warrant reiteration. I think the first thing is there’s a team sport element and there’s the need to build consensus and buy-in. Trevor, I’ve written seven books on digital transformation. I wrote one most recently called The Human Machine. But before that, I wrote a book about future-proof. Digital transformation and the experience economy was a focus. And the funny thing was is that technology projects, there’s something like a data point. You’ve probably seen this, they fail like half the time. And the interesting thing is technology projects, technology projects don’t really fail half the time. It’s people failures. It’s almost always, and as I dug deeper into it, the transformation from one generation of technology to the next tends to fail because culture tends to always be the resistant parts of the org that won’t embrace, won’t utilize, won’t implement, won’t participate. And of course AI is going to offer levels of augmentation and streamline and process efficiency that over time might remove some of that friction.

But it’s never really been like that these companies, technology doesn’t work. It tends to be more, it gets lost somewhere in the org. The salespeople won’t implement, input the data into the CRM, so the CRM doesn’t work well. The project management people don’t fill in their hours, and things like that. And you’re like, oh, this new project management system stinks. Well, it’s like, does it really? Or do people not use it? So what I’d also like to pivot, though, here is in your eyes, data itself, this is kind of a crossover question that gets to the heart of what you do, but also what the company does, analytics, AI, applied analytics, deep learning, machine learning, all this stuff, it gets conflated, but it isn’t really all the same. When it comes to your strategy and implementing, how much does data and utilizing the data and analytics drive your decision making, versus what we’re talking about with trend following and implementation?

Trevor Schulze: Yeah, it’s what old is new again, right? Everyone’s now focused in on the data, and maybe I’m in an echo chamber because I work for a data and analytics company and this is what I talk about all day, but if you think about data driven enterprise, which has been a hot topic for a number of years, you find that people are failing. They say they want to be a data driven enterprise. They want to make decisions based on data. They want to do AI now. And at the core of it, it’s around data management. It’s about the people. It’s about making sure that people feel comfortable with these new capabilities. And when I’m talking to my peers about data and analytics, we’re kind of at this inflection point where people maybe have taken a defensive thinking around data and analytics. It’s that hoarding mentality. It’s the new oil, it’s the oxygen of companies. And people are culturally resistant to unlocking access for everyone. And to your point you made about half of data or business transformations fail, I think maybe more. That percentage is going up because people need to really think about data governance, data management, data access. This is the oxygen of AI. If you have poor quality data, if you don’t manage your data, if you don’t know the access and availability and you don’t unlock this for everyone quickly, you’re going to lose. And I think in the sense of this conflation of data and analytics and AI, they all come together. And I think the stat that I just saw recently, we did a survey, we’re surveying everyone because people are like, “Hey, I can’t do AI unless I have good quality data.” Or, “Hey, I want to improve my data and analytics. What do I do? And I’ve got data everywhere. It’s huge, and I can’t get access to it.”

And the survey that, I’m looking at the quote right here in front of me, so I’m not that clever. So give me a break. 92% of organizations continue to invest heavily in AI and analytics, 92%. So pretty much everyone. And yet 19% feel that they’ve established a data driven culture. And that’s like an analytics gap. I’m going to call that the AI gap, because if you don’t have a data driven culture, if you don’t have data management, you don’t have a modern way of thinking about how to manage data and govern it and make it available to everyone, how are you going to do AI? How are you going to take advantage of this new paradigm shift? And so when I’m talking to leaders, I’m saying, you have to go on the offensive now. You have to think differently. You have to figure out how to quickly and safely enable people to get access to data just for analytics. But now the fire on the whole area now, or the gas on the fire I should say, is AI, and you can’t ignore it. And there’s a lot of things happening in our space that AI, augmented analytics are coming. And so we can’t sit around and wait and do things the old way. If you’re talking about modern IT strategies and you’re talking about business transformation, you better have your data and analytics strategy in line, or you better be making it real because you can’t get to AI effectively. I don’t care if you choose an LLM. Good, choose an LLM. It doesn’t mean your business processes are improved. Doesn’t mean that you’re using context within your own company, doesn’t mean that you’re going to be able to improve the people in your company without taking data seriously. And it seems like every five to 10 years, this topic comes back, to your point about do people enter the right data in their systems? Do people care? People are afraid of maybe putting data in the right place. So many different ways we can go on this topic.

Daniel Newman: Oh, absolutely. And the really interesting thing, too, is that data prep hasn’t become less of a thing in the era of AI. This is actually just an accelerator for those few and far between companies that really did a great job of preparing their data. And that’s one of the interesting things, is this hasn’t really, I mean, there are some generative or advanced tools that are improving how quickly you can prep data because of AI and being able to sort data and data types and do labeling and stuff. But companies that had a lot of that done were able to very quickly move towards more and more AI-centric workloads. Whereas other companies are like, to your point, it’s like, yeah, there’s some things that can handle, there’s vector and 3D and different database structures that can handle unstructured data, but those companies are far behind. They’re just not as prepared. So that’s, to your point, why constantly being on the good hygiene for data management is still really important no matter where you are in your AI journey. I’m really enjoying the conversation, Trevor. And I’d like to get to a couple things that you talked about here for our audience. And one of those is you had a set of predictions around how IT decision making is going to change. Can you share what those are?

Trevor Schulze: Yeah, and I am very deep into the data and analytics space, so I could go into other areas, but I’m sure you’ll have other guests that can talk about that. I think trends in IT decision making are going to be rooted in AI-powered analytics. It’ll become mainstream in 2024. Even our own Alteryx product has AI power behind it. We have products that are there. Every person in the space has that. I think augmentation, as I mentioned earlier, augmentation analytics is going to be a big thing. And what I mean by that is people are going to want to engage with their data differently. They’re going to want more user-friendly tools. They’re going to want access to data much more quickly. And we call it multimodal engagement. If you want to code, code. If you want to do low-code, use low-code, drag and drop. If you want to use natural language to engage with your data, that’s coming very soon. That’s very quickly. And so people’s ability to get access to data more quickly, their time to insight will speed up, depending on which way they want to go about it. People, to your point, are going to say, well, I’ve got hundreds of SaaS applications and I’ve got on-prem data warehouses and I use stuff out in the cloud and stuff is scattered everywhere. It doesn’t matter. The capabilities coming, I predict the capabilities coming are going to make it so that you’re going to be able to pull from anywhere very rapidly, and IT engagement’s going to go down because the barrier of entry is going down to access.

Now, people freak out with that and they go, “Oh, this is terrible. How are we going to be responsible and how are we going to be compliant and how do we ensure that people don’t steal stuff?” And so if we talk about the democratization of analytics, the democratization of data, it hits mainstream in 2024, and will become a known, understood, and agreed upon core strategy for companies. And it’s something that Alteryx has been talking about for years. Now every one of our competitors and one of these emerging startups are all saying democratization of analytics, democratization of data. It’s been kind of like marketing. And some companies like mine have done it, but now everyone is looking around and going, “Oh, shoot, AI is here. I better be able to get speed to insights around what I use digitally in this company.” And so the other trend I think that ties this all together is I think you’re going to see a lot of people realize that customers, employees, shareholders, are going to be asking CIOs for the responsible AI framework. What is their data ethics? What are they willing to do with their data? And you see some early movers like Microsoft and Google who have to. They are the cornerstone of people providing services around data and analytics and workflows and workloads. So I think the whole data governance and privacy piece will continue to be amplified. But I think the responsible AI framework, like if you are doing democratization of data and you have augmented analytics, people are going to say, well, is this non-deterministic behavior? Can I trust this capability? Can you explain to me how this AI thing in analytics gave me this answer? We have to think about the human agency and oversight.

It’s sort of like you’re just not going to see general AI around this stuff. People are going to get results from this co-pilot, and then they’re going to have to interpret it anyway, but it’s going to happen much more rapidly. And then you’ve got to prioritize privacy and security, reliability, safety, fairness, inclusivity. The trends are going to be this is here and you can’t ignore it. Every digital capability out there is going to say, we have AI. And you’re going to have to quickly deconstruct that and say, are we willing to use this? Is this something that we’re willing and able to share with our customers and our employees, that we’re doing this safely? And I’m the optimist again. I think we’re going to solve a lot of these problems. We’ve got a lot of people thinking about this, but as a CIO and as a buyer and as an IT decision maker, I start now with AI. Why would I buy anything that doesn’t have either it available or soon to be available? Because it will be the productivity multiplier above traditional paradigms of it.

Daniel Newman: So I completely agree. I don’t think you can be a CIO, I don’t think you can be a CEO and not be very, very significantly weighted into thinking about AI and its impact on your business, whether that’s processes and automation, whether that’s better decision making and data, or some mix of all of the above. I would think that if I was a board and I was listening to a CEO’s strategy and he didn’t have AI, maybe every 10th word or so right now, I kind of joke, but I’ve been to a lot of tech events this year, Trevor. So listen, we’ve only got a couple of minutes left. So I’m going to ask you a two part question and hopefully we can wrap up here. The challenges of implementing these types of solutions are palpable, and the go forward, it’s not just about implementation, but it’s about future-proofing. So what would you say to your peer group, the CIO peer group that are out there saying, how do we get this implemented and how do we make sure what we implement doesn’t become obsolete in short order?

Trevor Schulze: So when I think about future-proofing, it’s less about trying to predict the future, and it’s more about creating an ecosystem that’s robust, flexible, can adapt to the changes. Because you’re right, this is a rapidly evolving space, and I think people hesitate. They’ll be like, “Well, if I wait long enough, the right answer will come.” And I am in the camp of you’ve got to move. And you have to be flexible, continuously plan for what’s happening, stay out there, be out there and understand the landscape. This is your job, regular review your strategies and the technologies that you’re using. Know that your vendors are going to be supplying you with a roadmap that’s going to rapidly evolve because they have to stay relevant. So this is the new normal. The change in decision making is you can’t wait. And when you move, you also know that you better be flexible, you better adapt, you better not get yourself into a walled garden. This is why I say multi-cloud matters. You’ve got to diversify your cloud investments. You can’t rely on a single vendor or technology. You’re going to have to explain to the board that this rapid experimentation cycle is normal and needed to stay competitive.

And then the other thing I think about future-proofing is talent. I think this is so important. Everyone thinks about technology when they think about future-proofing. I think about the people. How do we future-proof our workforce? I am investing in talent and training. How do I cultivate a data literate workforce? I hear data literacy more now than I did in the last year. People heard data literacy from me, and it was like, I don’t know. Now it’s like, oh yeah, I need AI literacy. I need data literacy. I need people who are capable of rapidly adapting and adopting and adjusting. And the people that don’t get on board with this, the people who think they can get away with doing it the old way, are going to find themselves out of a job. And I hear that now. I hear like, oh, AI and augment is going to get rid of jobs. No, it’s only going to get rid of the people who don’t invest in themselves or are not working for organizations that invest in them. I tell people when I mentor them, you better be in an organization that has money and time set aside for you to learn. You have to have this growth mindset. You need to ensure that you’re leveraging new data and analytics capabilities, new AI capabilities. You need to be experimenting yourself. And that’s really important right now because it’s evolving so rapidly. If you don’t keep up, the train’s going to leave the station, you’re going to wonder why you weren’t on board. And so that’s future proofing for me, that flexibility around technologies, that diversification of multi-cloud and multi-capabilities, best in breed. And then Alteryx, we have a big thing about we believe that that’s what we do. But that talent piece is a whole different podcast, but I think it’s critical.

Daniel Newman: Yeah, that’s great advice and great inputs. We’ve seen a big trend line towards upskilling. Of course, we are in a world where I would say be in an organization that invests in you. Also be constantly investing in yourself. Tools like LLMs have given us a lot of democratized access to information. We’re in the YouTube training economy. We’re in the social networking, LinkedIn learning. I mean, I always say, if you can’t find something to consume every single day that makes you a little bit sharper, more aware, whether that’s in group settings where you’re with peers, whether that’s learning and leveling up through reading great content from the world’s most prolific thinkers and CEOs and educators and professors. Or if you’re a technologist, maybe even learning, getting more into the technical layers where you might be a project architect, but you get down and talk to the developers about what they’re experiencing and that stuff’s available to you. So it’s kind of that coupling, work with a company that’s supporting you, constantly be learning and supporting yourself. Make sure that you’re never obsolete. I absolutely think that’s a sage and very valuable piece of advice. And of course, get your data right, get your analytics right so that you can get your AI right. And I’m hearing you, Trevor, loud and clear. Hey, we’re out of time here, but I want to thank you so much for joining me here on The Futurum Tech podcast. I hope you’ll come back soon, and we can talk more about all of this and where we’re at with AI in the coming year.

Trevor Schulze: Oh man, I’m looking forward to this next year. Thank you for having me. It went quickly and I hope the audience got some few pieces out of this. And I’m looking forward to this next year, this next couple years. This is a moment in history that I think we’re going to look back on and just be just shocked how fast things change. And it’s a great time to be here.

Daniel Newman: Absolutely. All right, everybody, you heard it here. Hit that subscribe button. Check out all of the thought leaders and executives that join us here each and every week on The Futurum Tech Podcast. To learn more about Alteryx, check out the show notes. We’ll put the links there. Of course, come back soon and see us. But I’ve got to go for now. Bye-bye.