How the C-Suite Should Think About AI Today

Note: This is an automatically generated transcript, which may contain errors. 

Patrick Moorhead: Hi. This is Pat Moorhead and we are live here in Las Vegas at Splunk. conf 2023. Daniel, it’s great to be here, in-person event. You can just feel the excitement around us. This event, quite frankly, has some of the buzzwords, hottest topics that we talk about in our research firms today. Overall data, we’re talking security. What else is there? Oh, there is more, isn’t there?

Daniel Newman: Well, I mean AI, but no one’s really talking about that, so we’ll skip over that one.

Patrick Moorhead: Yes.

Daniel Newman: We’ll gloss over that one, he says sarcastically.

Patrick Moorhead: No, it’s literally what I think you and I are spending 90% of our time on these days.

Daniel Newman: Well, it’s horizontal. I’m starting to really put this thesis together about AI being digital transformation 2.0.

Patrick Moorhead: Yeah.

Daniel Newman: We saw a decade, everybody talking about digital transformation, digital transformation. Remember when we first started talking about that?

Patrick Moorhead: Sure. Yeah.

Daniel Newman: We had some good fun, you and I.

Patrick Moorhead: We did.

Daniel Newman: Had some good debates about it. But AI isn’t a technology adjacency. It’s a horizontal technology that’s really going to impact every part. So when you talk about data, you talk about cybersecurity, you talk about all these trends are going. We’re looking at how AI is going to overlay and make these things more productive, more efficient, more effective. By the way, it’s been a theme here so far at Splunk. conf.

Patrick Moorhead: Totally. And we’ve also talked the intersection between AI and security is huge as well. We saw some product announcements. So you know what? Let’s stop babbling and introduce our guest. Paul, how are you?

Paul Kurtz: Good. Great to be here.

Patrick Moorhead: Yeah, first time here on The Six Five. We really appreciate that. We appreciate you talking about pretty much the biggest topic out there today and that’s AI.

Paul Kurtz: Yeah. It is a lot of hype around AI, but it’s important that we have a lot of discussions about it.'Patrick Moorhead: That’s right. There’s hype, but there’s reality.

Paul Kurtz: Yeah.

Patrick Moorhead: There’s true value that I know your customers and many others can derive from it.

Daniel Newman: Yeah. I think the problem or the challenge or the opportunity, you can look at it positive or negative, half-full, my water’s still full, but is that for a lot of people, practitioners and people in the industry, Paul, is probably is you as well, this isn’t really new. Okay, I get it. There’s a tipping point, yes. AI is suddenly interesting to everyone. The boardroom is talking about it. The C-suite is talking about it. Your grandmother is at the dinner table talking about it. But maybe just first and foremost, what is your impression of this sort of wave that we’re seeing around AI as a Splunker?

Paul Kurtz: Yeah.

Daniel Newman: AI’s been part of this story for some time. What’s the demarcation between what’s cool and new and what’s just has been for a while?

Patrick Moorhead: Yeah.

Paul Kurtz: Well, I think everybody’s pushing things together. When I think about it, I think in first terms, machine learning. Machine learning has been around for a very long time, but then you hit November 30th of last year and ChatGPT comes out and the world is on fire with AI. And I think as I look at it, it’s one, we have to differentiate between machine learning and AI. Certainly, the prompts that you can use on ChatGPT and the others out there, it is eye-opening. One of the things that’s really interesting about this is because, well, ChatGPT and the like is in everybody’s hands now. It’s not as though it’s a technology that is limited to the few. It’s a capability that is available to everyone and I think that’s one of the reasons why we have so much, if you will, hype around the issue.

Patrick Moorhead: Yeah, it’s interesting. First of all, this reminds me a lot of when the web first hit and then e-commerce hit and then it was apparent that mobile was a thing and the stock prices of companies ebbs and flowed based on the strategy that they had and the opportunity. We saw that. What’s your web strategy? Well, what’s your e-commerce strategy? If you look at the companies that were disrupted in Web 1.0 and then in e-commerce, and then in mobile and social, I think we’re seeing the potential disruption today. So it starts off this board of directors to the C-suite and then everybody gets engaged. By the way, Dan and I love this because it creates a lot of demand for industry analysts to help them figure this out. But you work with end customers. You help them divide, help think through that. What are you recommending for them to come up with an AI strategy? I think AI, we believe, also encompasses the conditional if-then, it’s really analytics-based AI to machine learning, to deep learning, to now generative AI. What are you recommending?

Paul Kurtz: Within a company, it designates a person that is the broker, the leader for the adoption of AI. That’s job one.

Patrick Moorhead: Oh, I get it, an AI czar.

Paul Kurtz: Yeah, it has.

Patrick Moorhead: Okay. 

Paul Kurtz: Yeah. We have to do that. You can’t have companies within a company randomly adopting AI. That means the CEO needs to designate that leader. It’s not like the self-promoted leader. It’s like you’re the person that’s going to lead this effort, that’s going to establish a process, and there’s a lot of work out there. There’s a lot of material out there as far as processes go, but that’s job one. Designate someone to be the leader within the company.

Patrick Moorhead: Person with the X on their back, accountable to maybe the board or the C-suite, right?

Paul Kurtz: Yeah, someone that can pull the pieces together. When I look at it from a Splunk perspective, this is something that we have to talk through with our customers. This is not, oh, we’re going to push AI on you. We’re going to bring AI in, but we want to understand where our customers are coming from and there’s ways we can leverage AI capabilities to make their jobs easier, but it’s not jumping both feet into the pool. It’s like, let’s find those discrete areas where we can leverage AI and make their lives easier.

Patrick Moorhead: Are there any key parts of that strategy that are unique from, let’s say, a classic strategy creation where, hey, you have a vision, you set objectives, you have a strategy, you have tactics and we’re going to go? What are some of the unique elements, let’s say for generative AI, that makes this different from let’s say an analytics strategy or a machine learning or a deep learning strategy? What does that look like?

Paul Kurtz: The big challenge is it’s already there and it’s in everyone’s hands. How as a company do you adopt AI or leverage AI when you know anybody can sign up and begin to leverage generative AI? It’s there and that’s what’s different from everything else we’ve seen in a tech revolution. If I wanted to build a website or if I wanted to do it, I needed to be nerdy about it, but now we’re using natural language prompts with AI. That’s a totally different ball game. So from a company point of view, yeah, you can turn it off so to speak, or block it, but you go back to the process of educating yourself on any organization, on what are we trying to do with AI? What are our goals? Stuart Russell has a book called Human Compatibility, which is really, really good because it unpacks a lot of the issues around AI and gets at this idea of beneficial AI.

Patrick Moorhead: Right.

Paul Kurtz: Leverage AI in a way that it’s of benefit to the organization, but don’t just jump in fully into the pool. It’s a great read and it really unpacks a lot of even the science behind AI as well.

Daniel Newman: Yeah, it’s really interesting. I think what you’re saying is accurate and also very reflective of almost all technology trends. I remember having a very similar conversation around big data a decade ago or more where everyone’s like, “Where do you get started?” It’s like you’ve got to have someone in your organization like you mentioned a chief AI person. We then talked about having chief digital officers in that era because all these things are hyper-important to the enterprise. I think the thing we know is AI is going to make us more efficient. It’s going to make us more productive. I think there’s not a lot of debate about augment versus displaced. I think most agree. I know when I wrote Human/Machine, my book that was on the similar topic, we literally said the same thing. In every era, there’s this new wave of transformative tech and everybody, by the way, Paul, goes, “Is it going to replace us?” And it’s like, well, kind of. It will replace something you’re doing right now and it will create something new that we’re going to need more people to do next.

We’re in that early phase right now where there’s a lot of panic, there’s a lot of uncertainty, but there’s also a lot of excitement and a lot of opportunity. For someone like yourself as an executive of Splunk, but also as a customer and interfacing the talks regularly at these companies, I guess give me that. One is, are you seeing the companies go forward? Are they hiring this specialist on AI and after they hire, what are the recommendations that you’re combining with these folks to make sure that they’re getting off to a good, fast, meaningful, measurable start with AI?

Paul Kurtz: Yeah. It’s interesting because last year, post-November 30th, I had the thought that it’d be really interesting to get customers around the table and just throw AI into the middle and just see what they would say and it was fascinating. They jumped in like, we’ve got to get our hands around this. There was a level of angst. I call it AI anxiety because as I said before, there’s a certain inability to control it, so to speak, and leveraging it. You can block it, but that doesn’t mean you’re not doing it on your phone.

Patrick Moorhead: That’s right.

Paul Kurtz: It’s how we proceed forth. I think there’s a requirement to, as I said, designate someone to lead, but also to start doing the reading of material that’s going to actually help you guide through it. There isn’t the how-to guidance. It’s having that broker, getting yourself smarter on AI and deciding how you want to leverage it and bring those efficiencies into your company whatever it may be.

Patrick Moorhead: Paul, I’m sure you’ve combed resources about AI and you have a lot of experience doing this as well, but what would you recommend resources to start, how to think of AI? Maybe customers or end users who aren’t as sophisticated or maybe smaller, they just don’t have access to the resources. Where do they go to learn more about this?

Paul Kurtz: It’s funny. I start with one book and it leads to another and leads to another and leads to another. There is a lot of really interesting work out there. If you want to start at that top level, there’s AI And Our Future, which is by Eric Schmidt and Henry Kissinger. It’s that top level of, what does this mean for us going forward? Then you can get Max Tegmark and Life 3.0 is far more technical. If you’re a leader in a company, you need to not just look at the front page of New York Times and Wall Street Journal and Washington Post. You need to dig deep. You need to try to understand it and understand the potential benefits and risks associated with AI. I could go off on all sorts of material. There’s actually a fascinating book, which is really eye-opening. It’s AI 2041, which is a cool mix of a sci-fi-like vignette story followed by analysis of, well, what’s the technology behind this? What does it look like? Kai-Fu Lee and unfortunately, I’m spacing off on the other author.

Patrick Moorhead: Yeah.

Paul Kurtz: It’s really, really interesting read.

Patrick Moorhead: No, that’s great. We should make sure we put those on the show notes.

Daniel Newman: Yeah, absolutely. But it sounds to me like your guidance is, be curious.

Paul Kurtz: Yeah, absolutely.

Daniel Newman: Ask lots of questions, connect with those that are doing, understanding. I think we know this, but the tool set is vast. I love sharing and you pick on me about it, but a lot of these great visuals now, look at all these generative tools. Because we talk ChatGPT, Bard, maybe we say Lama, but we’re acting like there’s three or four and there’s tons of generative tools. There’s many more large language models. And of course, as the continued development of large language models, smaller models are going to become more and more valuable and more efficient. I actually think we’ve agreed for enterprises, the large language models are going to be somewhat table stakes. Everyone’s going to have access to them. It’s going to be, what’s that unique enterprise data set that you have that can help drive CX?

Patrick Moorhead: That’s right.

Daniel Newman: That can help drive cybersecurity?

Patrick Moorhead: And what you do with it in the end. What I loved about where you started too, which is most of our conversations start at the tech level, but what you were really giving insights into is, hey, when you’re coming up with that strategy and your vision for it, think big. Think more blue sky than what’s here and now and what you can do today. Because what we can do today is going to be eclipsed in five years of where this is going. Shoot ahead to where you want to go. So I’m thinking, my big takeaway, and I used to run corporate strategy for a very large company, is have a five year, maybe a 10 year vision of where this could go in the end state and then come back. Just given the radical change, it seems like you have to do this to be able to be ahead in five years as opposed to perpetually behind and reacting to what you see today.

Paul Kurtz: Yeah. I agree. The way I think about this is from a business perspective, how can I leverage AI to increase efficiency to better deliver for my customers?

Patrick Moorhead: Yes.

Paul Kurtz: That’s the departure area and it’s not jumping in wholly. It’s like, how can I leverage this to provide more capability, more value to my customers? That’s like that human-driven, beneficial AI application. It’s not jumping into the pool. It’s like, okay, start small and you look at some of the things that Splunk is doing. It’s not that we’re jumping into the AI pool.

Patrick Moorhead: Right.

Paul Kurtz: In fact, we’ve had a lot of it around from machine learning and now we’re using natural language prompts for our SPL query lookup. You don’t have to necessarily code all that. You can do it. That’s a great start.

Patrick Moorhead: Yes.

Paul Kurtz: You’re not turning the universe inside out. You’re just leveraging AI where it’s appropriate.

Daniel Newman: Well, Paul, I think that’s a great place to wrap up. I’ve really enjoyed, I’d say we’ve really enjoyed this conversation. It’s going to be really interesting to come back to this six-, 12-, 18-months and it’s moving very fast. It used to be like, oh, we’ll look at it in three years. No. We’re going to have to look at it in like three months.

Paul Kurtz: Yeah.

Daniel Newman: Because even if you look back at just the adoption wave, the tools, the advancement, what you’re seeing is probably a seminal moment in terms of the future of every enterprise and every business. Hopefully, a lot more of these customers are listening to what you have to say, Paul.

Paul Kurtz: Yeah. Thank you very much. It was a pleasure being here.

Patrick Moorhead: Sounds good.

Daniel Newman: Alright everyone, thank you so much for tuning in here. We are at .conf 2023 here in Las Vegas. We appreciate you joining us for this one. Hit that subscribe button. Watch all of the sessions with Patrick and myself of The Six Five On the Road. For now, we got to go. We’ll see you all soon. Bye-bye.