1 00:00:00,080 --> 00:00:02,680 Speaker 1: Engines for growth. Ken Rogoff of Harvard sat in your 2 00:00:02,720 --> 00:00:04,280 Speaker 1: chair at the start of the week and he said 3 00:00:04,320 --> 00:00:05,920 Speaker 1: he's not sure where growth is going to come from. 4 00:00:05,960 --> 00:00:08,240 Speaker 1: That's an economist. You're running a business. Where's the growth 5 00:00:08,280 --> 00:00:08,880 Speaker 1: coming from. 6 00:00:09,160 --> 00:00:11,119 Speaker 2: That's the difference between someone runs a business right and 7 00:00:11,160 --> 00:00:15,880 Speaker 2: an economist. Look, I mean, we've talked about AI all 8 00:00:15,920 --> 00:00:18,720 Speaker 2: week long. It's a big opportunity for us, and I 9 00:00:18,760 --> 00:00:22,280 Speaker 2: think that you'll just continue to see new opportunities emerge, 10 00:00:22,320 --> 00:00:24,880 Speaker 2: things we don't even understand yet and applications that we 11 00:00:24,920 --> 00:00:26,760 Speaker 2: haven't seen that are going to take advantage of what's 12 00:00:26,800 --> 00:00:28,800 Speaker 2: going on in AI over the next six, twelve, eighteen 13 00:00:28,840 --> 00:00:33,040 Speaker 2: twenty four months. Cybersecurity is an incredible area of investment 14 00:00:33,080 --> 00:00:38,120 Speaker 2: for our customers, particularly as generative AI helps the bad 15 00:00:38,240 --> 00:00:42,320 Speaker 2: people be worse people and make them better at what 16 00:00:42,360 --> 00:00:44,879 Speaker 2: they do. And we have to really come together as 17 00:00:44,920 --> 00:00:47,400 Speaker 2: an industry and work hard to protect our customers. 18 00:00:47,400 --> 00:00:51,000 Speaker 3: So cybersecurity is a big one. I think all of. 19 00:00:50,920 --> 00:00:54,760 Speaker 2: Our customers continue down this journey of thinking through how 20 00:00:54,760 --> 00:00:57,520 Speaker 2: their applications are architected and where they reside. Are they 21 00:00:57,520 --> 00:00:59,360 Speaker 2: into cloud, are they in the private cloud, public cloud, 22 00:00:59,360 --> 00:01:01,360 Speaker 2: which public clod or am I consuming them as a 23 00:01:01,400 --> 00:01:05,199 Speaker 2: SaaS application? And you know, hybrid work is still in place. 24 00:01:05,280 --> 00:01:07,200 Speaker 2: There's there's still a lot of positive out there. 25 00:01:07,280 --> 00:01:09,120 Speaker 4: How many years have been you've been coming to Davas? 26 00:01:09,440 --> 00:01:11,600 Speaker 4: This is my eleventh, Okay, so it's been eleven years. 27 00:01:12,040 --> 00:01:14,160 Speaker 4: This Davos feels a little bit different, like people are 28 00:01:14,200 --> 00:01:15,760 Speaker 4: actually just trying to get a lot of deals done 29 00:01:15,760 --> 00:01:17,520 Speaker 4: and try to figure out exactly what to lock in. 30 00:01:17,800 --> 00:01:20,040 Speaker 4: Do you get that feeling too well? 31 00:01:20,080 --> 00:01:23,200 Speaker 2: I think somebody asked me earlier about whether this felt 32 00:01:23,200 --> 00:01:25,840 Speaker 2: like a normal Davos, and I think it seems busier 33 00:01:25,880 --> 00:01:28,920 Speaker 2: first of all this year, and I do think there's 34 00:01:29,000 --> 00:01:32,920 Speaker 2: a lot of there's a lot more tangible business discussion 35 00:01:32,959 --> 00:01:35,640 Speaker 2: I think going on than you might see normally. But 36 00:01:35,680 --> 00:01:38,280 Speaker 2: there's also a lot more There's a lot more to 37 00:01:38,360 --> 00:01:40,920 Speaker 2: talk about with all the complexity going on. And you've 38 00:01:40,920 --> 00:01:44,440 Speaker 2: got elections, You've got you've got the Middle East situation, 39 00:01:44,600 --> 00:01:46,920 Speaker 2: You've got Ukraine, you've got the are we going to 40 00:01:46,959 --> 00:01:49,800 Speaker 2: cut rates? You've got Ai. 41 00:01:50,000 --> 00:01:51,360 Speaker 3: I mean, it just goes on and on and on 42 00:01:51,400 --> 00:01:52,920 Speaker 3: and on. There's just so much to talk about. 43 00:01:53,200 --> 00:01:55,360 Speaker 4: What's going to affect your business most? I mean, are 44 00:01:55,360 --> 00:01:59,000 Speaker 4: you expanding more in certain regions to avoid some of 45 00:01:59,040 --> 00:02:00,600 Speaker 4: the conflicts that you keep seeing. 46 00:02:01,000 --> 00:02:02,040 Speaker 3: Or are you basically just. 47 00:02:02,040 --> 00:02:03,960 Speaker 4: Sort of keeping an eye on all of this and 48 00:02:04,000 --> 00:02:06,200 Speaker 4: then chugging forward with continuing to try to hire the 49 00:02:06,200 --> 00:02:08,400 Speaker 4: best cybersecurity people and move forward with all of the 50 00:02:08,400 --> 00:02:10,480 Speaker 4: different programs that you've been working on. 51 00:02:10,880 --> 00:02:14,919 Speaker 2: Yeah, I would say that we're investing in areas where 52 00:02:14,960 --> 00:02:17,520 Speaker 2: we do see growth. We're investing a lot in AI, 53 00:02:17,639 --> 00:02:20,000 Speaker 2: We're investing in cybersecurity the same areas that I talked 54 00:02:20,000 --> 00:02:24,280 Speaker 2: about earlier, in which regions, in which regions. It's pretty 55 00:02:24,680 --> 00:02:26,079 Speaker 2: I'd say it's pretty well balanced. 56 00:02:27,200 --> 00:02:28,760 Speaker 3: The AI specialists tend. 57 00:02:28,600 --> 00:02:31,160 Speaker 2: To get hired where we have engineering hubs, so that's 58 00:02:31,240 --> 00:02:35,120 Speaker 2: you know, first and foremost. But we've also, because of 59 00:02:35,120 --> 00:02:36,800 Speaker 2: what we saw in the pandemic, I think every company 60 00:02:36,880 --> 00:02:40,919 Speaker 2: has been diversifying geographically relative to their supply chains so 61 00:02:40,960 --> 00:02:43,440 Speaker 2: that you know, as we've talked about before, no one 62 00:02:43,440 --> 00:02:46,679 Speaker 2: ever designed a supply chain expecting an entire country to 63 00:02:46,720 --> 00:02:48,760 Speaker 2: shut down, so we had to make some changes to that. 64 00:02:48,880 --> 00:02:51,080 Speaker 2: We continue to work through those kinds of things. 65 00:02:51,200 --> 00:02:53,519 Speaker 1: You've been going through a big transition quite a while 66 00:02:53,880 --> 00:02:57,040 Speaker 1: going towards software. So what's recounting revenue. We've been talking 67 00:02:57,040 --> 00:02:58,800 Speaker 1: about this for years to get we have. It's that 68 00:02:58,880 --> 00:03:01,600 Speaker 1: transition complete. Now comfortable, you're. 69 00:03:01,680 --> 00:03:02,880 Speaker 3: We've made a ton of progress. 70 00:03:02,919 --> 00:03:08,120 Speaker 2: When we get the Splunk acquisition completed, we'll surpass twenty 71 00:03:08,160 --> 00:03:11,040 Speaker 2: billion in software sales as a company, which puts US 72 00:03:11,040 --> 00:03:12,200 Speaker 2: somewhere in the top six seven. 73 00:03:12,240 --> 00:03:15,280 Speaker 3: I don't know, something like that. But there's still more 74 00:03:15,280 --> 00:03:18,320 Speaker 3: to do. There's still more software. 75 00:03:17,880 --> 00:03:20,800 Speaker 2: Assets we can build organically, probably some inorganic stuff we 76 00:03:20,800 --> 00:03:21,040 Speaker 2: can do. 77 00:03:21,560 --> 00:03:22,440 Speaker 3: But at the same. 78 00:03:22,240 --> 00:03:27,400 Speaker 2: Time, with the AI explosion, we're a significant recipient of 79 00:03:27,440 --> 00:03:31,560 Speaker 2: the infrastructure benefit underneath the GPUs in both the web 80 00:03:31,560 --> 00:03:34,359 Speaker 2: scale as well as ultimately in the enterprise. So our 81 00:03:34,400 --> 00:03:38,760 Speaker 2: hardware business, which in some cases has subscriptions associated with it, 82 00:03:38,800 --> 00:03:39,600 Speaker 2: in some cases do not. 83 00:03:40,320 --> 00:03:42,160 Speaker 3: We think that both of them can grow over the 84 00:03:42,240 --> 00:03:43,000 Speaker 3: next few years. 85 00:03:43,160 --> 00:03:44,720 Speaker 1: This is a tough question to answer, but do you 86 00:03:44,760 --> 00:03:47,800 Speaker 1: think investors have fully internalized your view on where things 87 00:03:47,800 --> 00:03:49,760 Speaker 1: are going and your message. 88 00:03:49,920 --> 00:03:52,120 Speaker 3: I think they've internalized the message. I think they're just 89 00:03:52,240 --> 00:03:52,600 Speaker 3: looking for. 90 00:03:52,720 --> 00:03:54,440 Speaker 2: One of the things that we've talked about is that 91 00:03:55,080 --> 00:03:58,040 Speaker 2: this transition to software should give us more predictability and 92 00:03:58,120 --> 00:04:02,880 Speaker 2: less volatility, and we've seen that come into play, but 93 00:04:02,920 --> 00:04:04,960 Speaker 2: we still probably have a little bit too much, and 94 00:04:05,040 --> 00:04:09,040 Speaker 2: so we've been rewarded for what we've accomplished. And I 95 00:04:09,080 --> 00:04:11,000 Speaker 2: think as we continue to do that and we continue 96 00:04:11,000 --> 00:04:13,440 Speaker 2: to deliver, you'll see that in the future. 97 00:04:13,600 --> 00:04:15,440 Speaker 1: You know from bankare for a couple of days. Everyone 98 00:04:15,440 --> 00:04:17,719 Speaker 1: wants to be a part of the AI story. What 99 00:04:17,839 --> 00:04:21,240 Speaker 1: surprised us, I speak for myself, what surprised me last 100 00:04:21,320 --> 00:04:24,440 Speaker 1: year is how quickly it became real. It wasn't just 101 00:04:24,480 --> 00:04:26,840 Speaker 1: a story that companies were selling. It was something they 102 00:04:26,839 --> 00:04:29,880 Speaker 1: were monetizing. And the growth was exponential in some cases, 103 00:04:29,920 --> 00:04:32,000 Speaker 1: and video a great example of that. Can you walk 104 00:04:32,040 --> 00:04:34,479 Speaker 1: us through on way you're seeing actual, real tangible growth 105 00:04:34,560 --> 00:04:36,400 Speaker 1: right now off the back of what's developing. 106 00:04:36,720 --> 00:04:39,039 Speaker 2: Yeah, I've actually told my team you're not allowed to 107 00:04:39,160 --> 00:04:42,640 Speaker 2: espouse about AI unless you follow it with a tangible 108 00:04:42,800 --> 00:04:45,719 Speaker 2: way that we're implementing whatever you were talking about, because 109 00:04:45,720 --> 00:04:49,520 Speaker 2: there's so much noise in the system. Look, I think 110 00:04:49,560 --> 00:04:53,479 Speaker 2: if we're building the infrastructure that's going to support underpinning 111 00:04:53,480 --> 00:04:57,760 Speaker 2: all the AI networks. So that's happening today. We're running 112 00:04:57,800 --> 00:05:00,919 Speaker 2: pilots right now with webscale players. We're working we're working 113 00:05:00,960 --> 00:05:04,440 Speaker 2: on a lot of design around future integrated stacks that 114 00:05:04,480 --> 00:05:06,080 Speaker 2: we're going to take to the enterprise to help them 115 00:05:06,080 --> 00:05:10,640 Speaker 2: do it. Secondly, we're looking at how we can deliver 116 00:05:10,680 --> 00:05:14,200 Speaker 2: a better customer experience for our customers by leveraging jen Ai, 117 00:05:14,240 --> 00:05:15,560 Speaker 2: which everybody, every. 118 00:05:15,400 --> 00:05:16,960 Speaker 3: Company is or should be doing. 119 00:05:17,880 --> 00:05:21,680 Speaker 2: We're building security assistance as an example, to help customers 120 00:05:21,760 --> 00:05:24,040 Speaker 2: navigate all the security tools you have and actually make 121 00:05:24,120 --> 00:05:26,520 Speaker 2: sense of a lot of it more rapidly. We're doing 122 00:05:26,520 --> 00:05:30,880 Speaker 2: the same in collaboration. We're transcribing meetings and so there's 123 00:05:30,880 --> 00:05:32,960 Speaker 2: a lot of stuff that's going on right now. But 124 00:05:33,000 --> 00:05:35,960 Speaker 2: I do think some of the greatest applications we have 125 00:05:36,080 --> 00:05:36,840 Speaker 2: no idea what they are. 126 00:05:36,880 --> 00:05:39,560 Speaker 4: Yet, which is something definitely that's been a theme. 127 00:05:39,640 --> 00:05:42,200 Speaker 3: To say is early. I say early. 128 00:05:42,720 --> 00:05:46,320 Speaker 4: One thing that's early maybe is that HPE is coming 129 00:05:46,360 --> 00:05:50,479 Speaker 4: for you more aggressively. They bought Jennifer Networks last week 130 00:05:50,520 --> 00:05:51,960 Speaker 4: and they said that they're going to be able to 131 00:05:51,960 --> 00:05:56,440 Speaker 4: compete more directly with you. So what's your response. 132 00:05:57,040 --> 00:05:58,160 Speaker 3: We love good competition. 133 00:05:58,800 --> 00:06:00,799 Speaker 4: What's your what's your way? It's your way of getting 134 00:06:01,200 --> 00:06:03,719 Speaker 4: some of the market share in a highly competitive market. 135 00:06:04,080 --> 00:06:07,039 Speaker 2: Look, I think that we have competed with both HP 136 00:06:07,680 --> 00:06:10,479 Speaker 2: and Juniper in the past, so I don't know that 137 00:06:10,560 --> 00:06:13,120 Speaker 2: it changes a lot for how we think about competing 138 00:06:13,160 --> 00:06:13,440 Speaker 2: with them. 139 00:06:13,440 --> 00:06:14,000 Speaker 3: To be honest,