is going to go down. And when it comes to the clients that I work with, I typically don't get a lot of calls. And that is because from a financial planning perspective, we've built that in. So when they turn on the TV and they see that the market's going a little crazy, they're not going a little crazy. I want my clients to feel very comfortable that we've already built this into the plan with Chelsea and Fidelity.
Fortune guests, please welcome MPW editorial director and Fortune Daily host Ellie Austin.
Hello everyone. Good afternoon and welcome to the 2026 Fortune Most Powerful Women Summit. It is amazing to see you all here. I can see lots of familiar faces. I can see lots of new faces. And also, it's the first time in our history that we have been here in beautiful Santa Barbara. So, I hope you get to enjoy some of the surrounding nature as well.
So let's be honest, it's been quite a year since we all met at last year's summit. There's been geopolitical tension. There's been economic upheaval. And there's been tech innovation at a rate faster than I think most of us could possibly have imagined. And as AI continues to reshape entire industries and the world that we live in, in the process, the old definitions of leadership and influence are being rewritten in real time. And so that's why we as the MPW team chose as this year's theme for the summit the new blueprint for power.
Of course, I say this every year, just as important as what happens here on the main stage is what you bring to every room. What happens in the corridors? What happens on the eco hike? What happens at dinner? So, make sure to ask questions whenever we turn to you and say hello to the person next to you. I know not many of you need encouragement doing that. You're an incredibly...
So, before we get into our first session, a few reminders. Everything that is said here on the main stage is on the record. And the same goes for our sponsors. Thank you so much. DoorDash, Fidelity Invest, Novartis, Salesforce, and Thrivent.
There's going to be a bit more clapping because we also have some partners. So maybe save your clapping until the end of the list of partners, just in the interest of time. So, we also want to say a big thank you to Block. Go Block. Indeed, Johnson and Johnson, Lincoln Road, and Bevy, who is our official hydration partner, and they have the cute little high-tech drink stations that you will see scattered around the hotel.
Okay, so who makes this summit happen on the Fortune team? First of all, my incredible co-chairs, Fortune senior writer for finance, Cheryl Estrada. She's also the author of CFO Daily. You're going to see Cheryl on stage this afternoon. MPW editor Emma Hinchliff, who many of you know because of her MPW daily newsletter and her amazing features in the magazine, and Fortune leadership editor Cla Zilman, who has flown in from London to be with us for the next three days.
And then, of course, we have an incredible new guest co-chair this year. She is a global tech executive, a former Fortune... who are going to be joining us on stage over the next three days. Actually, I said two, there's three because I missed my boss, the editor-in-chief. So, editor-in-chief Allison Shantel. You're going to be hearing from Allison in a second. She's interviewing Ruth Porat.
Executive editorial director Diane Brady, who's sitting down here. Many of you know Diane. And then I don't know where she is, but my fellow Fortune editorial director Kristen Stiller. Hi Kristen. Your support means so much. You're all brilliant moderators and we are so lucky to have you as part of this team.
My final thank you, and then I promise it's done from me for now. The MPW ambassadors, who are a remarkable group of around 15 women who are longtime members of this community. I can see you scattered throughout the room who really help us with everything in the run-up to the summit. And they are essentially, I think of them as our co-hosts. So they're going to be floating around. They have a particular color of lanyard. I think it's green. Meetra has green. And if you're a newcomer...
So, please welcome to the stage Ruth Porat and Allison Shantel.
if we execute AI, figure out where are we in the buildout, what's holding us back from meeting that opportunity, and how we can realize it. So my first question is, you joined Alphabet in 2015, and in 2016 the company just says, it declares, we're going to be AI first, we're going to make this platform shift, and you start putting the pieces in place to do that. So you had a front row seat to watching a company get ready for the era we're in now. What were the key decisions that you saw that were made that set it up to meet this moment?
Well, actually, it goes back to 2010. And I would say it even goes back earlier than that. When Google went public, a core part of the founders' letter for the IPO was we will invest in long-term growth. And we were always very deliberate about what that meant. So even at a company as innovative as Google, we said let's create organizational structures to nurture entrepreneurial innovation above and beyond everything we're doing in our business. So we created something called the 20% project where if you had a great idea, you could go off and pursue it. Why am I going back to that?
One of the first things that came out of the 20% project was Google Brain, which was our first AI business. In 2014, we acquired DeepMind, and then only in 2016 did we say, you know what, now is the time to really pivot from being mobile first to AI first. And I think one really important lesson from that is you must invest for long-term growth. By the time you need it, it's too late to say, 'Okay, now we're going to start. It's 2016.'
So when our CEO Sundar Pichai said, and in 2016 we are pivoting to AI first and it will be a full stack approach, at the time it wasn't really clear what that meant, but the foundation was already there. It was an extraordinary research team, it was...
Amazon is spending more, and with the four horsemen of tech, it's about $730 billion going into the AI buildout this year. I'm curious, I know you're in a quiet period or entering one ahead of Q3 earnings, so you can't get too specific, but as you're thinking about long-term investing, how far into that long-term investment are we? Are we going to be looking at the size of investment continuing to need to be poured in for multiple years, or are we kind of at the peak?
So, there are a couple parts to that. One, we've said publicly that we're looking at about 200 billion of capex this year and that we expect that will increase significantly next year. And we've also said, as have a number of our peers, that we are capacity constrained. The demand for compute, because of the value that our partners are seeing in the enterprise, in governments, what we're seeing across our platform suggests that we're in the buildout here now. If you could snap a finger, we could deliver value. That's an important point.
But I bet if I did a show of hands, everyone here would say, 'But we're so early on the journey.' And I think that is true. Many of us are still grappling with, if you do triage on the full set of opportunities within our enterprise, where can we get the highest return? One of the things that struck me is when Demis Hassabis won the Nobel Prize, and you and I have talked about this, he was embarking on something that had been a 50-year grand challenge, and that was to predict the protein structure for all proteins known to humanity.
This comes back to your question. And at the time, it took four years for just one protein. There are 200 million proteins known to humanity, and members of his team said, 'How is this even possible?' And his answer was, 'Why not?' And his answer when he was awarded the Nobel Prize shortly thereafter, four years later, was the benefit of this technology is that we can solve the most intractable problems that we have in each one of our businesses, government, wherever it happens to be.
That suggests that really the magic in this, and the answer to your question, is how deeply do we dig into sort of creativity about how do you expand the scale and scope of your business. So we do see this as an opportunity that extends for quite some time. Point number one.
Point number two, each of us, to generate an attractive return on investment, need to be focused on two things. One, what is the value that we add to partners so that you can actually deliver attractive revenue growth, and the other is how efficiently do we deliver that compute capacity. And so on everything from model efficiency to infrastructure efficiency, we have historically and continue to be very focused on driving greater performance per dollar of investment.
So, you know, a lot of funding these things though come down to the right timing, the right demand, all of it working out all at once. When this was 2008, you had a front row seat to a financial crisis at the time you were at Morgan Stanley. Soon after that, you became the CFO of Morgan Stanley. And liquidity was a big vulnerability. We're entering an era where a lot of debt is financing this AI buildout and that AI data center buildout at a time when there is uncertainty. Sometimes the buildout is not happening as fast or we're not able to move as fast as we want.
When you kind of look back at your experience from 2008, what are the biggest risks you see in the system now? Are you worried about the amount of debt that's funding this? Not from someone like an Alphabet, you guys are clearly fine, but from the larger ecosystem.
So, it's interesting you use the word liquidity. When I arrived at Google back in 2015, I was asked a lot about the financial crisis. Probably one of the most meaningful roles I played in my career was advising then Secretary of the Treasury Hank Paulson. And one of the key lessons from the financial crisis was that you should identify your greatest source of vulnerability early and fortify against it, because you can't address it in the moment. Now, for banks, it was liquidity. Without liquidity, you couldn't run a trading operation. Without liquidity, you shut down.
And I've been asked that question frequently since. What is the greatest source of vulnerability today? I think for all of us across industry, one of the most important elements is innovation in your business. Because if anyone is connecting with your customers in ways that you are not, because they are using AI and you are not, or if anyone in your industry is looking at how to manage supply chain or other elements, you're at a competitive disadvantage. So that's one part of it.
I appreciate that's not what you were asking. You were really going to, but what about this question about funding and financing? And I would say one of the important lessons there from other platform shifts is it is imperative that each one of us is delivering differentiated solutions. I ran technology banking at Morgan Stanley in the late 90s, and what you saw going through the late 90s is those that really kind of sustained growth over the long term were those who were using technology in a differentiated way.
At the time I said, if you're using the internet just as a way to have an online catalog, that's not a sustainable differentiator. Similarly today, if you're using AI simply to try and extract efficiency from a business, that's nice, but that's not long-term sustainable. The real question is what should be different? What is available today that wasn't available previously?
One of my favorite examples on that, probably because I spent so much of my time in my career in financial services, is in financial services. If you think about the service that was delivered to ultra-high-net-worth individuals for decades, it wasn't available to everyone else because the cost of delivery was too great. But with AI and agentic AI, the ability to actually aggregate more information, deliver insights in a more cost-effective way, means unit economics have gone down.
You can deliver for an entire customer base you previously couldn't deliver for. That is better for everyone in society, that everybody is getting access to quality information. But most important, when unit economics can change, you can identify new markets that you maybe wanted to identify in the past but couldn't. Which is why I think that Demis' comment that we should each look at the most intractable problem, a market you wanted to address, a way you wanted to deliver that you couldn't, and this will make a difference for it.
I'm curious, when you look at what winning looks like for Alphabet, do you need to fund this so that you play to win and you have the best model and the best chips? Do you have to kind of own that ecosystem, or at your scale is just being good enough enough as you're thinking about financing it? Where is the priority for you?
So I think the word win in the context of this technology platform is an important one to drill down on. Oftentimes it's viewed as where are you at any particular point? There's third-party leaderboards that gauge sort of where are you on reasoning or logic, math, etc. Our view is the most important element is to, if you want to call it win, lead in responsible deployment of technology, because the thing that is true throughout history is anything that is not built for the long run won't endure for the long run.
And so in our view, the single most important thing we're focused on—well, the single most is three. So the three most important: if we don't collectively fortify the downside risk, collectively we will not have the opportunity to capture the upside. And you've hit on one part of it, but I think very importantly where we've been focused literally since we said we're shifting to AI first is one, what about governance around models?
So concurrent with announcing we're moving to AI first, mobile first, moving to AI first, we said we're going to develop and operate with a code of principles, and since then have been very focused on what's the governance framework that is needed to provide the responsibility, the scientific rigor, the resilience that's needed with a technology that continues to evolve.
And our colleague Demis Hassabis, again, the Nobel Prize-winning scientist, amazing leader, has codified that, really bringing in what across Alphabet we think is the most important way to approach this, which goes to levels of transparency, testing models before release, bringing in a whole of community—government, developers, those of us who are model builders out at the frontier, etc., academia—to actually have a rigorous foundation. That's one part of it.
The other part of it is how to ensure when you're building the infrastructure to deliver this, it's done responsibly. And the third part that's super important, you and I have talked about it, is ensuring that this upside benefit actually addresses the needs across economies, across society, so that we're narrowing inequities in society, addressing inequities. So again, it builds something that is sustainable.
So what I'm reading between the lines is thinking for the long term, building this in the most responsible way will be the way to win. You could probably also look at that and say, well, there's maybe people that are building it a little bit recklessly and a little bit too fast.
There always are in platform shifts. Fortunately, I think hopefully the market shakes that out.
I just have one other question kind of about a macro trend, and then I want to dive into some of the energy limitations we're facing. But there was a study from Jefferies over the weekend that basically said the most likely long-term outcome of the AI boom will be a massive capital destruction in the US. And the reasons that they stated were basically that market share is going to cheaper open-source models away from the things like the Anthropics and the OpenAIs. There's still lots of demand and Gemini potentially, but China open-source models are drawing a lot of users.
And then hyperscalers are financing data centers at a time when the continued demand for closed models could be in question. Like it's still very high, but maybe it could come down. I'm curious what you think of those trends. Like, you know, I take it you probably disagree long-term the opportunity is there financially for this to make sense, but for those two trends, is open source at risk and could that really hurt the ecosystem?
