Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: Antonio Nearer joints us Here, CEO of HPE. Antonio, thanks
Speaker 2: so much for joining us here talk to us about
Speaker 2: what are the key issues for you guys going forward
Speaker 2: here to this AI story is a story that's playing
Speaker 2: out across the tech stack.
Speaker 3: Well, good morning, Paul, thanks for having me. Yes, of course,
Speaker 3: today the narrative is all around the AI and the
Speaker 3: ability to use AI to change the world. And so
Speaker 3: for us as a technology company is how we accelerate.
Speaker 4: The deployment of AI in the enterprise.
Speaker 3: And today we talked about the you know, the evolution
Speaker 3: of just large language models, introegantic models, which allows you know,
Speaker 3: to increase productivity across the entire enterprise, cross processes and functions.
Speaker 3: And so we have made that series of announcements here
Speaker 3: which brings together the infrastructure, the software, and the cloud
Speaker 3: experience into one integrated, unified operated model including governance and compliance.
Speaker 3: So that build the trust with an enterprise to go forward.
Speaker 1: And how does this change your growth trajectory going forward?
Speaker 1: I know that you know one year out might look
Speaker 1: very different from five years out versus ten years out.
Speaker 1: Just walk us through how you see this changing what
Speaker 1: you had anticipated to what you now think you can achieve.
Speaker 4: Yeah, ask Caarli.
Speaker 3: So if you go back and read our earnings and
Speaker 3: Q two, we grew the company as a whole forty
Speaker 3: percent year over your own revenues, and we expand our
Speaker 3: margins because of the content that we bring into Our
Speaker 3: revenue now has a bigger mix of networking, software and
Speaker 3: cloud services, and in that context, we believe networking is
Speaker 3: going to be the thesis of our company. If you
Speaker 3: think about developing these frontier models, whether proprietary or open
Speaker 3: source models, you need a lot of GPU power. That
Speaker 3: GPU needs to be very productive, you don't want to
Speaker 3: keep it idle, and the bottleneck of that is networking.
Speaker 3: And so we have now with the acquisition of Juniper,
Speaker 3: an amazing portfolio in the three key.
Speaker 4: Elements, scale up, scale out, and scale.
Speaker 3: Across, which position us to be core element of that
Speaker 3: infrastructure build out. So this is why we believe the
Speaker 3: company is going to grow double digits going forward and
Speaker 3: will continue to expand operating margins, and that will translate
Speaker 3: in free cash law. So we already guide it, which
Speaker 3: is unlikely and you know in many cases for six
Speaker 3: quarters ahead, So think about it because of the confidence
Speaker 3: we have in a growth trajectory.
Speaker 2: Antonio, where do you think this technology, this AI technology
Speaker 2: story is. I mean a lot of folks are saying
Speaker 2: we're still in a very very early innings, but you
Speaker 2: just think about the amount of CAPEX that is being
Speaker 2: spent by a variety of players within the sub stack.
Speaker 2: It's just extraordinary. Where do you think we are in
Speaker 2: that comparim there of AI investment.
Speaker 4: I concur with that we're still early.
Speaker 3: And Paul, what you have to understand that is three
Speaker 3: customer segments you have to look into it. Number one
Speaker 3: is the model builders and the hyper scale is the
Speaker 3: neo clouds. We're building large amounts of compute capacity. We
Speaker 3: believe by the end of the decade, we're going to
Speaker 3: build two hundred and fifty gigawad of power that will
Speaker 3: host these gibus and that's the cape you're talking about it.
Speaker 3: But then ultimately, what is the mix of the capacity.
Speaker 3: It's going to be shifted from training models to influencing models,
Speaker 3: and that's where we're going to see the large adoption
Speaker 3: of you know, AI into the enterprise to drive that productivity.
Speaker 3: But if you put an context of industrial revolutions in
Speaker 3: the past.
Speaker 4: This actually is very small.
Speaker 3: Compared to that spend that was done, you know, in
Speaker 3: every inflection point, including the turn.
Speaker 4: Of the past century.
Speaker 3: So yes, I understand the concern about the montal capex,
Speaker 3: but when you're put it in context of changing the
Speaker 3: way we work, the change in our society will still
Speaker 3: small relative to that.
Speaker 1: You know, just looking at how you might be deploying cash.
Speaker 1: I know that you tap the debt market in March
Speaker 1: to refinance some upcoming maturities. You've got strong liquidity with
Speaker 1: cash and equivalents of more than five billion dollars at
Speaker 1: the end of the second quarter. What might prompt you
Speaker 1: to go to the debt market again to raise more money.
Speaker 3: Well, we do that very regularly because remember inside the
Speaker 3: HPE we have an operating company. Obviously we are paying
Speaker 3: down the debt and refinancing where we need to, and
Speaker 3: that's the operating balance sheet you're referring to. So our
Speaker 3: balance sheet is super super strong. And then we have
Speaker 3: the financing company, which has thirteen billion dollars under asset management.
Speaker 3: Think about the finance that we do for cass stomers
Speaker 3: and we do it also surpass of the asset lifecycle
Speaker 3: management services, and basically we have debt securities against those assets,
Speaker 3: but the return on equity on that is super high,
Speaker 3: super super high, So we use those vehicles when it's necessary.
Speaker 3: But what we announced just at the beginning of this
Speaker 3: month in our earning is is that we're going to
Speaker 3: pay down that debt much faster.
Speaker 4: In fact, we.
Speaker 3: Expect a return to two times leveraged by the end
Speaker 3: of this fiscal year, which is one year ahead of plan,
Speaker 3: and we're going to start returning seventy five percent approximately
Speaker 3: over free cash flow in twenty twenty seven to shareholders,
Speaker 3: which we expect to generate at least four point five
Speaker 3: billion dollars in individends.
Speaker 4: And share buybacks. That's how we're going to return it.
Speaker 3: So we are very strong, and that comes back to
Speaker 3: the question you asked me before, where it comes from
Speaker 3: the growth and the operating margets