Bloomberg Audio Studios, podcasts, radio news. Let's talk about this markets because things have been going crazy. We talk about an SMP in an ASDAC right now around session lows I was looking at the Philadelphia Semiconductor Index down seven percent on the deck.
Yeah, it's pretty brutal out there. It's not just chips, it's also some of the AI plays. We were speaking earlier about some of those AI darlings getting hit with some short reports. So investors coming out and saying, I'm sure at the stock and this is why, and that has lumen, for example, has gotten hidden in part of that?
Yeah?
Absolutely, And it raises the question super micro, symbiotic, a lot of these other names here. I don't know. Is this just a symptom of the fact that these were the high flyers, So hey, if you made a lot of money off them and you're stealing skittish, why not just cash out? Or is this more symptomatic of people rethinking that HOLYI.
Trade or with the idea of say super micro, is that now it's not in the small caps, it's in the SMP. So does that change who covers it and how they look at it? And that changes how you view the numbers. But either way you're laughing at me.
I'm laughing because it's some day we have to talk about why super Micro is even in the SMP five hundred. That's a whole on the topics, right, But.
That's also why the analysts can now look at it in a different way, and then you have different analysts covering that stock, and that winds up hurting. It does raise the question in terms of the AI trade, what a cyclical what a structural role? And then how do you invest in that? Sam palm Asano, chairman of the Center for Global Enterprise and former CEO over at IBM, it joins us. Now, Sam, it's really good to get
your perspective. We very much appreciate this. How do you how does someone who's been in the technology industry for decades and understands innovation and understands a business cycle, what is AI right now?
Well, that's a great question, Alex, and remain good being with you guys. Again, it's always a pleasure to be with you, especially in a beautiful afternoon. It's great to be in my office not outside playing golf or something. But on a more serious note, now, I think that the best way to think about this that I can draw parallels to the Internet if you like, but when they're still in the early stations of AI. And if you go back to the early days of the Internet,
what happens in phases. It begins with the enablers, and that would have been back then that's scage on Cisco and AT and T. Today you would put the enablers is the Microsoft and videos, AMD, anthropics, the chip guys, et cetera, the foundational model guys. And then it moves
to the adopters over time. But that's time and that if they go back to the Internet, that would have been Meta Amazon, DoorDash, Netflix, and then the next phase with the people people that apply the innovation to the technology, and that would be the ubers, the Netflix of the Airbnb's et cetera, et cetera, in door dash, you know. So that's the phases of this thing and so far to repeating itself. And we are in the early phase,
there's no doubt about it. So the enablers are going to continue, to my opinion, anyway, do well now, I mean, you guys know markets. I can't speak to evaluations of what happens day to day but long term trends. I've seen this thing. I saw in the early days of Client So I've been at this industry a bout fifty years, so this isn't my first time to kind of view these transitions.
So, Sam, is the real boost and efficiency going to come from Romaine and I using it on our phones, or is it going to come from like entirely new business lines and re thinking the way we fundamentally do.
Things, Alex, I tell you that's a very interesting insight because if you look at what's going to happen short term, if I quote the Kinsey estimates of this sort of thing, they value the GENAI that's got the adoption in the early stages of it in four key areas. That's customer operations, marketing and sales, software engineering in R and D. I ete productivity in the word, so they're saying the first
phase will be productivity. That also could be productivity to the user on the phone, by the way, as far as their user experience booking, reservations or whatever it happens to be, it could be simplified by the application of ANI. But in the enterprise itself, it's going to be more around productivity Now having said that, the real innovation comes, real value creation comes in the next phase. And I go back to my analogy to the Internet. That's what
I mentioned earlier. Uber, Airbnb, Spotify, Netflix, That is the next phase where this thing is going to take off.
Go ahead, Yes, so you're seeing a lot of paly. I didn't mean to cut you off, but I want you to kind of on that because, I mean, your experience is relatively unique. I mean, you came of age at least share in your career at IBM at a time when corporate computing was really taking off, then personal computing.
You were still there when the sort of the Internet age came about, and now you're not with IBM anymore, but you're still around here investing in what a lot of people think is going to be that next big new technology. I don't think anyone is doubting that this might be the next big thing. I think people are kind of doubting who the winners and losers are going to be. And right now all the bets seem to be with such a small core the companies.
Well that's I mean, that's exactly right, and that's how it was. To go back to the Internet, it's a small core that benefited initially and then it broadened out, and it broadened out when it got to the adoption phase,
not the enabling, I mean the infrastructure build out. That's why these guys are sold out, because everybody's chasing the infrastructure buildout, I EI the hyper scalers, and they're ordering GPUs and chips lay crazy because they want to be ahead of the curve as this adoption phase or demand increases on the cloud providers Amazon, Google, Microsoft Is or et cetera, et cetera. That's kind of where we are in the phase. I really do think that the hard
thing to predict, I mean go back in time. Even in the early days of Internet when companies were digitizing, did people think it will be impacting how you take a ride in a car a uber or get a room someplace, or get videos media to place and all that sort of stuff from music? Nobody really conceived in the early days of the Internet. It was more about digitizing things and putting your information up from the web
and maybe doing a little bit of commerce. Did anybody think that a little bit of commerce would be Amazon? So the point is now your point is predicting where it will go. I'd tell you that's really I'm not an investor in this space, and you know, we're focused primarily in areas around healthcare and around cyber and those sorts of things.
And you're seeing the substantive use or potential use of this technology. Because even when you go back to the Internet age, and I know there was a lot of hype and a lot of folks who were predicting things that never panned out. But I think for a lot of us, at least the layman out there, you can actually see the tangible qualities of what they at least were trying to build. AI just seems a lot more Ephemerald.
Well, I mean, there's a couple of things. First of all, let's take about the Let's talk about the enterprise adoption. Right where can great value can be created in these enterprise companies and s Guys running these companies realize they've done the pilots, they've experimented, they've done these things, and they're going to chase productivity in the short term, but they're going to drive innovation in the long term. And
that's the innovation and the enterprise. There are still limitations in the technology I mean, for example, accuracy and transparency and validity. If you're doing financial services, or you're doing national security, or you're doing healthcare and you're worrying about people that are going to live or die, you need those issues to be addressed, and they will be addressed. And there are a lot of startups trying to address a lot of those and those areas of inadequacy that
exist today. So therefore you see things being applied to what I called a simpler use case like marketing, like customer service, et cetera, et cetera. You believe that now these cycles, as I go back to the Internet, they're like ten to fifteen year cycles, you know, right, So I mean we're in the year what three maybe depend upon how you count this stuff. So I mean we have a long way to go. And from an investor, I mean I'm basically a VC today. I'm not involved
in large companies. I'm an advisor, but I'm not really involved day to day. Fundamentally, from a VC perspective, we're making bets in those industries where the technology you can have a massive impact, for example, the delivery of healthcare or therapeutics and those sorts of things, massive impact, to improve the system, to drive productivity, to improve outcomes that
could be significant. Financial services. There's a lot of things that can be done in financial services again to improve the value to society and value to the companies themselves.
All right, Sam, have to leave it there, great insights, as always, have a wonderful day.
Sam.
Paul Masano is the chairman of the Center for Global Enterprises. He said, a vc funder in the AI space, and of course a long time IBM employee EU rose to the top of the mountain there