Live at the Pure Accelerate Summit in Las Vegas

21:54How has the product development world changed since the AI boom began? Yeah, so I think there's a couple different big areas of transformation. The first was, you know, Pure built a really killer product, and it was great to simplify the way storage was managed. We realized pretty quickly that customers were looking to buy a platform to reduce silos, enable better workflows, get a better understanding and representation of the data. And as we've evolved, I think everyone's come to recognize that data is at the core of everything now. AI has really brought that to the forefront. And in doing so, we really needed to be able to rationalize the infrastructure stack in a very different way than what it had been seen before.

22:32And that's really kind of our mission. Our mission is to make the data be a core, enable it to be rationalized by AI, and so customers can get the biggest value they possibly can out of it.

22:42Carol Massar:How are you seeing, though, companies be more discerning in terms of what they want to spend on, what they want to do, and what they're saying? Well, okay, we'll do this, but what's our payoff, or how quickly do we get there? Yeah, so the ROI TCO discussion is pretty much totally at the forefront for any of these big investments. I think AI is... Is it really... TCO, you mean total cost of ownership? Yes. And is that a significant change before you go into it from maybe six months ago, 12 months ago? We're definitely starting to see people wanting to rationalize the value that they get to the solution consistently.

23:13I think what they're seeing now is, am I making the right investments that give me the agility to be able to execute effectively? That one's probably become more of the forefront in the last six to 12 months. If you think about the way things are changing, AI pretty much every six months is a completely different world. All new innovations are being built. And so you have to build a framework of which is super agile and can move with you. And so you definitely don't want to lock yourself into a corner in these ones.

23:38Carol Massar:What do you mean it's changing? What specifically do you mean? Sure. New models come out, new capabilities, new workflows, new ways of accessing data and different mechanisms. If you look at what we're talking about here at this show is we're talking about data becoming primary, data primacy. If you think about that world that exists today, architectures were built in a very different computing era. It was built in an era where compute was assigned to applications. Now we're really starting to rationalize that AI needs to have understanding of context of everything in order to truly make decisions and execute effectively.

24:10So that's part of the training to inference conversation, which is something that we want to talk to you about. I'm just curious about how the inference part of this is changing how customers are thinking about storage and data infrastructure. Yeah. So everyone wants to get value from these models. They have lots of power, whether they build a small one or a large language model that's out there as a foundational model. They want to use their data, though. They want to have the data be representative so they can run workflows. As an example, if you build an agent that actually executes a task, like a profitable order, as an example, only approve profitable orders, they need context from many different systems.

24:44It's not just the one system creating the quote. They need to know the supply chain. They need to know how it's manufactured. They need to know the total cost. That context is siloed today in many different applications, and it requires human integration. but these agents only effectively execute with consistent shared context. And that's the big change that's happened these days is people are realizing while the power's there, the data is not ready for this, and they need that shared context. They need a system of record that's understanding across all these applications. And that's what's really changed lately.

25:16Carol Massar:What about security, though? Can all data easily be shared across the platform? Is there a need to be those protective silos for stuff? So what's even worse is people are taking agents and connecting them to all their apps, which has no security or governance really built around it. It's just kind of opening it up altogether. When you build a shared context model, you can apply governance there and controls to what has access to what. And that's really the big win is you can start having agents do workflows but govern the way they access the data below. Do you think the private sector is going to be way ahead in terms of governance issues versus governments and global governments?

25:51Carol Massar:Or is that like a really silly question, like naive? No, no, I think everyone's kind of going after a similar methodology, right? They all want to be able to access their data more effectively. I think they're challenged by the way things have been built in the past. And so now everyone's got to try to do things differently, and it's not an easy path to get there. We built this thing called an enterprise data cloud. It was a vision to help customers on that journey. It was helping them get rid of storage silos first. It was helping them build autonomy around operations so they could execute more effectively.

26:18And now we're bringing this data intelligence layer, which allows them to rationalize their data holistically. Yeah, I'm wondering about the competitive landscape out there. And as you know, you're by VP of products, so you need to build something that is different than what's out there. Build something that keeps customers, attracts new customers. You've got Dell EMC, HPE, NetApp, the hyperscalers, Vastata, among others in different parts of the business. What does your product pipeline look like to make your offering unique? Yeah. So the first and foremost is we've just had a simpler product holistically from the get-go.

26:53We then built an abstraction layer on top of that to make it like a cloud-like experience. That was what many people went to the cloud for originally, but we made the simplicity in operating the architecture. The big, though, win, which was today's or this show's big announcement, was being able to rationalize data outside of EverPure, meaning that our data intelligence layer can access all data everywhere without the customer having to send us all the data. This is a big difference in our architectural approach. Most people say, give me all your data, and then I'll help you rationalize it. We are not saying that.

27:26We are saying, hey, it will work really great on our systems, and we built an amazing cloud to deliver that with our enterprise data cloud. But we can help you understand where your data, what your data is, where it exists. That is a very different approach than anybody has really gone after, and that's what we're doing with our universal data intelligence.

27:42Carol Massar:So I am curious, Chad, what does it mean from the investment perspective? Because I think about the things that certainly our audience, an investing audience, and are watching the spend by certainly the hyperscalers, the energy component. There's a lot of moving parts here. How does that change maybe the investment story? I think our opportunity here is pretty massive in just scaling the company beyond what we're traditionally known for, which was just storage infrastructure and building clouds for customers. I think now being able to rationalize the data, we not only move to new personas and new buying centers, such as the chief data officers and those entire teams, which we weren't previously talking to, but opens up an even broader ecosystem of development on top of the substrate for next generation applications.

28:21So I think it brings us into a couple of new massive areas that we didn't have access to.

28:26Carol Massar:Oh, go ahead. But more broadly in the investment space of what we all talk about and the build of data centers and the demand for chips and all the components. Like, does that all still make sense to you based on what you guys are seeing and what your clients are needing from you, but then that bigger picture? I think we've become a close, close partner with the computing folks in the infrastructure area because we have that rationalization of data. People are going to want to pair that with the NVIDIAs and other computing infrastructures that allow them to be able to get that value out of their data as they build these next generation applications.

29:00I'm wondering how day-to-day in your life and in your world you're actually using AI. Yeah. Oh, a multitude of areas. So I have agents doing research that send me every single morning kind of a download of what's going on in the competitive landscape. I have them sending me ideas on how I can change my workflows to actually make them more optimized. Are they good ideas, though? Oh, it's hit or miss. And what's funny is you can say this one kind of sucks, right? Like give me something a little bit better. And it will actually automate and change the way that they actually do things. I use it quite a bit in content creation.

29:32So I have a version of me that writes exactly like me, and so it helps me be able to get content out faster. When we write PRDs for product development, it goes through and scores it as whether it's actually a good one or not based upon the feedback I many times get from engineering. We use AI in development of new dashboards to understand our own business in a more dynamic way. It's really an interesting model because we create a very core data structure within our environment. And then we use AI to rationalize it, not through your traditional analytics environments, but actually just using natural language to ask it questions to give me answers to data versus me having to create dashboards to look at it.

30:12Carol Massar:I mean, how long in your career have you been talking about AI? And how is it so different, how things have dramatically changed and how it feels like the acceleration of change is pretty massive. It's pretty massive. I think the newer and newer models, especially in software development, have gotten unbelievable. They've gotten to a next level. We've been into AI since early days. It was like 2016 when we did our first partnership with NVIDIA. We built a stack with compute NVIDIA GPUs with our storage. And that was more around your traditional machine learning. This whole generative model world is a whole other world altogether.

30:51And so I think we're using it inside the products. So when we say we're building autonomous infrastructure, we're using AI to actually take customers' telemetry data and help them make decisions because they can no longer run at human speed anymore. You've got to run at machine speed now. And so in that case, you're getting recommendations and you're saying, yes, I'd like to do that. Over time, you say, don't ask me anymore. Just go do that. So no question it is making you more productive. Oh, my God. Tons. I'd say we rate our PMs comically enough on like, you know, you're two times a PM from all the way up to 5X PM for people who are using all these various different types of tools, right?

31:27And so we're helping to grow them in this space so that they get more productivity. And we have different results than what we would have had if we had to try to do these things manual for analysis and the like. You're listening to the Bloomberg Business Week Daily Podcast. Catch us live weekday afternoons from 2 to 5 Eastern. Listen on Apple CarPlay and Android Auto with the Bloomberg Business app. Or watch us live on YouTube. As we mentioned, we are at Everpeer Accelerate 2026 here in Las Vegas, talking about how AI is resetting the economics for storage, power, cloud, and more. We've got Tarek Robiati with us, Chief Financial Officer of Everpeer.

32:03He's a$25 billion market cap provider of enterprise storage solutions. Tarek, good to have you on the program today. You were CFO of Hewlett Packard Enterprise. You were CFO of Sprint. You've got a master's of science in nuclear physics and electronics. So there are a lot of different directions we could go.

32:18Carol Massar:I feel like an underachiever. I'm just going to put it out there. Well, I do want to start with, like, really the – we talked about this with Charlie a little earlier, the big theme of memory prices. Yes. I mean, because this is what you have to navigate as CFO of the company. Demand for splash storage. It's driven prices higher. Margin concern for customers, though. So it's been a boon to some public companies, including Sandisk, Western Digital, Micron, among others. Component cost inflation, how is that changing the Everpeer story? So it has changed not just the Everpeer story, but it has changed the entire industry.

32:53Because what we're witnessing is a CapEx super cycle. And effectively, if you look at the next three years, and if you consider the cumulative CapEx spend of the hyperscalers, just that group, So the estimates vary, but in total, the number that most people would agree is about$3 trillion. $3 trillion over the next three years. That's two times the defense budget. So it's quite extraordinary the amount of money that goes there. And then off that figure, I've excluded the AI titans, so the likes of Antropic, OpenAI, and so on. And then you have other players, you know, near clouds, players like Cornweave and Crusoe and others.

33:37So the demand is real. And so effectively what happens is that the supply is tight and the industry has to adjust and rebalance the supply-demand equation. And that's what we've gone through. So it is a change that is not temporary. It will revert back once more capacity becomes available. but we don't see that demand supply imbalance abating before the first half of calendar year 27.

34:07Carol Massar:2027. Yeah. What will the prices look like then? To be honest, no one knows. Right. And it really will have to revert back to the mean. How quickly will that be is a big question that everybody's asking. But that is typically what happens. And maybe there is a new mean as well. It may not be back to exactly the same level either because the world has changed, and now Silicon is much, much more in demand than ever before, and that's the practical reality. So how do you as CFO kind of think about your own needs within your company and balancing the spend where you do overspend because you need to be in it versus holding back?

34:50Carol Massar:Because these cycles, right? There's a ramp up, and then prices come down. You've just got to kind of find your way through. So how do you navigate and how do you make choices right now? So the trend was very sudden and rapid and started to materialize at the end of last calendar year. And you probably heard it from Charlie that the cost of NAND jumped by about 600 to 800 percent. Now, we are lucky because, by design, I should say, we're lucky to have a great team of engineers at Everpure that have design solutions that use a limited number of components, and those components are managed by way of software.

35:32So when you really look at how much of our cost base is truly dependent on components, it's only about 17 % of total revenue of the company. So that's a big plus. That's a massive plus. So when you are having to face a very large increase on a relatively small proportion of your cost base, You can withstand the shock, but this is not something that was easy by no means. So, sorry. Well, what about customers withstanding the shock? Totally. Because I'm curious about demand elasticity here, product delays among enterprise customers, or is AI infrastructure modernization remaining so strong that pricing has really not affected demand materially?

36:15No, no, you're spot on. So we can withstand the shock, but we have to pass a sum to our customers, no question. And we did, but we wanted to share the pain. And so what we have done is we've taken a very intentional approach to the way we priced. Our price increases were more gradual than the competition, and they were also of a lesser magnitude on a cumulative basis. And the reason why we did that, it was very strategic. It was effectively, you know, we did not want to profiteer from the crisis. We wanted to make sure that we manage the business for the long run. Customers have long memories.

36:50They won't forget certain things. And so what we have done is we wanted to make sure, to your point on demand elasticity, that we don't get to a point where we're testing levels that are unacceptable from a customer standpoint. And so we are very careful in the way we handle pricing. And we are operating and we've chosen to operate at the lower end of our historical gross margin range. Our gross margin rate has been between 65 % and 70 % on products, and we are operating at 65.5. So really at the bottom, that was intentional because we wanted to make sure that we managed the business for the long run and protected the franchise.

37:31Carol Massar:So what do you give up in order to be able to do that? As CFO, where you have to maybe make some choices. Exactly. And that is about the trade-off you make between having more profits in the short term or more growth in the short and longer term. And we chose, I was a strong advocate that we needed to keep our market share take a stance and continue to grow the business and grow the top line. That's why we grew 35%. So carry that over to clients and customers who are thinking about how much do we spend with you and other companies and entities within kind of the AI build-out. trying to figure out their own ROI and where to spend.

38:10Carol Massar:Take us there. Yeah. So whenever you look at an industry that faces very sharp price increases, what tends to happen with customers who have still the need to spend is there's a flight for quality. And the reason why this is particularly important for the AI revolution that we are entering is that your return on investment is measured over the long run. Therefore, if you invest today, choose carefully and choose the best possible product from a quality standpoint that withstand the test of time. Because the estates that any one of our customers has continues to grow from a fleet standpoint. They have greater and greater data needs all the time.

38:52And therefore, they have to revert to solutions that will be there with them for the long run. And that's where we come in. I want to shift the conversation a little bit to talk about revenue mix. It's sort of where you see that going. The business has shifted. If you look back at fiscal year 2020, subscription revenue was only 25 % of total revenue back then. Now it's more than 46 % in the most recent fiscal year. How high does that get? I quite like the fact that we are balanced between products revenue and subscription revenue. That's really, really important. We like the fact that subscription revenue is at about 46%, as you pointed out.

39:27But we want to continue to grow product revenue. And the reason why that is is that product revenue measures your ability to really penetrate the market and to really expand your market share. Subscription revenue gives you more certainty, more rateable revenue, more certainty on free cash flow in the future. So we need a balance on both. Right now, I would say 54, 36 is actually a good mix. I like it that way. So as is, is good. And investors and analysts should say, think to themselves moving forward, it's going to look like that. if all goes according to plan over the next couple of years. It'll continue like that.

40:02Yes, and also the thing that we have to reckon, and you know when you move revenue that is to a rateable revenue, then you're going to dilute your revenue growth. And the fact that we're growing in totality and on both is a really good sign for our company, and I'm very pleased with that as CFO.

40:19Carol Massar:I want to go back to conversations you guys are having with clients because as everyone continues to play with AI, It's got some CFOs, as you know. Again, I'm going to go back to concerned about their own budgets. Uber has set usage caps after it blew through its AI budget in just four months. So what are the patterns you're seeing? Are your customers kind of moving away from experimenting with the technology to budgeting for recurring spending? Are we starting to see more of that happening? That is very hard to tell you. I would say you see a bit of both. You still see budgetary expansion. And you also see experimentation.

40:58And that's also why our Evergreen One offer, which is an SLA-based offer, whereby you subscribe to a contract that delivers specific levels of performance, is great to cater for those customers who still are uncertain about their budgets and how they want to go about continuing to experiment.

41:17Carol Massar:So they have to hit certain performance targets? We have. We are accountable. We are accountable by contract to our customers to deliver a certain level of performance. and the customer can ignore the box that delivers a performance and just judge us based on what we deliver for them. And it's a subscription contract that has different terms depending on customer choice and it helps them experiment and doesn't force them to buy something that they may feel is more expensive. And so you have both. You have customers who go for higher quality systems, they have more defined plans, and you have customers who are still searching for what they want to do and we help them both of us.

41:55We're always trying to figure out where we are in this cycle right now. I mean, and you have to look at projections. You have to understand where we are and where we're going. Is this a cycle, or are you confident that today's demand is durable and sustainable rather than a temporary infrastructure build-out? I think it's a super cycle. I firmly believe that this isn't a short burst. I think there is real demand underpinning it. I mean, I go back to my estimate on hyperscalers. it is only representing roughly 90 % of their operating cash flow, meaning they can afford it.

42:29Carol Massar:But just because you could afford something doesn't mean you should spend. Oh, totally. Totally agree. But they have very clear plans. Of course, you know, I mean, my broker budget is never an authorization to spend. I was just going to say. But I'm pointing to you that they have a lot of great plans. Right. Their spend and the estimates that brokers have about them point to the fact that they represent about 90 % of their operating cash flow. They're not stretching their balance sheet. That's where the uncomfortable zone for a CFO comes. And they can do that. And, you know, if you believe in the AI story of what you can do in terms of changing the world, which most people do, and increasingly do more, then, you know, you can accept that this is not a short burst.

43:11It's there to stay. Stay with us. More from Bloomberg Businessweek Daily coming up after this.

43:41biotech companies with high R &D spend, small cap stocks with improving operating margins, or the S &P 500 minus high debt companies. Chances are there isn't an ETF that fits your exact criteria. But on public, you just type in a prompt and their AI screens thousands of stocks and builds a one-of-a-kind index. You can even backtest it against the S &P 500. Then you can invest in a few clicks. Go to public.com slash market and earn an uncapped 1 % bonus when you transfer your portfolio. That's public.com slash market. And paid for by Public Holdings. Brokered services by Public Investing, member FINRA SIPC.

44:18Advisory services by Public Advisors, SEC Registered Advisor. Crypto services by ZeroHash. Sample prompts are for illustrative purposes only, not investment advice. All investing involves risk of loss. See complete disclosures at public.com slash disclosures.

44:32Carol Massar:When you own your own business, you own every decision. Now own the card that rewards you for it. The Chase Sapphire Reserve for Business card brings the best Sapphire Reserve benefits to business owners who expect hardworking rewards. Designed to meet the needs of business owners at scale, this pay-in-full card elevates your travel experience and offers premium benefits and value toward business services that will take your business to the next level. Fuel your business and maximize rewards with 8x points on all purchases through Chase Travel, 3x points on social media and search engine advertising, annual partnership credits, and more.

45:07Carol Massar:Make every journey more rewarding with a$300 annual travel credit and access to a network of airport lounges, whether you're looking for pre-flight productivity or time to rest and recharge. Chase Sapphire Reserve for Business. It's the card that gives back all you put in. Learn more at chase.com forward slash reserve business. Chase for Business. Make more of what's yours. Accounts subject to credit approval. Restrictions and limitations apply. Cards are issued by JPMorgan Chase Bank N.A., member FDIC. Dog grooming genius here. Most people see a busy dog salon, but I see operational excellence.

45:44Thanks to Genius from Global Payments. Scheduling? Personalized. Checkouts? Instant. Absolutely genius. From game day crowds to every groomer in this shop, Genius keeps everything flowing seamlessly. Schnauzer is styled. Flawless execution. Big league reliability for any business. That's Genius. You're listening to the Bloomberg Business Week Daily Podcast. Catch us live weekday afternoons from 2 to 5 Eastern. Listen on Apple CarPlay and Android Auto with the Bloomberg Business App. Or watch us live on YouTube. We are at Everpeer Accelerate 2026 here in Las Vegas, talking about how AI is resetting the economics for storage, power, cloud, and more.

46:27We're talking industry leaders, customers, and partners to understand the shift.

46:31Carol Massar:We are indeed. And one of those leaders is Michael Cardesi. He's the CEO at FedHive. He is here with us in Vegas. Welcome, welcome. Nice to have you here with us. Oh, great to be here. This is awesome. I love it. It is awesome. We were just talking before we got going how much we're kind of taking everything in and just hearing the perspective. Mike, first of all, tell us about your company and what you guys do. Yeah, sure. So FedHive is what they call an accelerator for compliance. Government, as you know, DOD, Federal has all types of compliance issues. We shepherd people through that process and get them to an authorization, an ATO.

47:05Most folks have a tough time getting a sponsor nowadays because of budget cuts, et cetera. So we manage that whole process for companies since that's not usually their core.

47:13Carol Massar:Has it become more interesting, more complicated? Is your phone ringing off the hook because of AI? Yeah, well, you know. Or just in general? Well, just in general because of all the security issues that are coming up. And then, of course, with AI and the pressure from security and all the attacks on an accelerated rate, How do we have the compliance issues associated with what the government wants, right? Because commercial space has one thing, but the government has these compliance. Is the government moving quick enough? I mean, this is the question. And David Sachs was AI czar for this administration, also the crypto czar.

47:47There has been a lot of discussion just in the last couple of weeks about Anthropics and Mythos and the government's reaction to Fable 5, its latest version of Mythos 4, with the quote-unquote guardrails and the jailbreaking there. Yep. Is the government moving quick enough? So the government is a big beast, and it is moving faster than it's ever moved before. It is. So I will say for the 10 years that I've been working in compliance, way faster than it's been before. But is it ever fast enough? As long as they're staying just ahead of the front of the wave, yes. But with Anthropic and all the other issues that you're talking about, they're bringing up more and more concerns.

48:27What are the concerns that that brings to you? So for us, we're working, even though our customers pay us, we really work for the government, right? So we are trying to make sure that they're happy and they're aware of what's going on. And that's the biggest issue. Yeah, I guess the question that I have is if you're working with a private company, you're not having to work with the government. You don't have to move at the speed of – you can move at the speed of private enterprise. That's right. Moving at the speed of government is a completely different story. So are you dealing with antiquated systems, antiquated rules and regulations, antiquated technology?

49:05Yeah, so we're right in the middle of this kind of firestorm of make compliance easier, keep the security high. We've got these new things accelerating through. We want innovation into the government. How do we get that without lowering the bar of security? So all of those pieces are coming into play.

49:21Carol Massar:When it comes to guardrails and protecting all of that data and information that is being collected and thrown into AI models and played with and hopefully coming out with some ROI at the other side of it, what can we learn from sovereign AI and what's going on that can be applied more broadly? That's a great word. That's been being banded around more and more of the sovereign data discussion. So the government requires everything to be inside of a boundary. You have a playground and you can do everything in the playground, but nothing can leak out. But we have these interactions with all of these different services from the hyperscalers and all those products.

50:00That's what makes it really difficult because in the commercial world, like you said, you can use whatever you want, try it out, break it fast, figure it out. But in the government, a lot of PII in the federal side, a lot of personal information, personal identifiable information. And then on the government side is their data, too, where you have real kinetic issues, right? So all of that data is really sensitive. And you can't really afford to make that break fast, kind of move forward kind of thing because the data is too expensive.

50:32Carol Massar:So no lessons to be learned? Oh, so the government's always been trying to be more conservative and not allow the data out as fast, which then goes to the, you know, how do we get more innovative stuff in? And so there's this push-pull all the time. That's part of the problem. And there's a lot of lessons being learned. Yes. Well, I'm curious about China and Gulf nations, for example. You bring up the sovereign AI discussion, Carol. And we can't have this discussion in a vacuum. We're only thinking about the U.S. Right. So in terms of what China's doing, in terms of what the Gulf nations are doing, what other countries around the world are doing with this technology and with this AI, when you When you understand what the U.S.

51:13government is doing, does it seem like we're in a competitive position with how we're handling it? Well, the U.S. government really forces us to keep everything in our boundary, in the continental U.S. boundary. Chips and everything. We work with the ITAR, the regulations for putting chips outside of the U.S., so we work with the Commerce Department and that sort of thing. So we are always trying to keep the technology inside of our... Does that constrain you in a way that other countries are not constrained? Well, yeah, because you don't have that multinational kind of amalgamation of these different countries doing all this work.

51:55We have to keep it inside of our shores. So, yes, technologically that could affect us, but the security aspect of the technology is something that we're worried about.

52:07Carol Massar:Hey, Mike, some of the conversations that we've had to – is what's going on at the kind of C-suite level, board level. What are the conversations that leaders at companies or institutions should be having at a very senior level when it comes to compliance and security, especially with all of the work that's being done in AI at those institutions? Yeah, most of the discussions that I'm having when I'm talking to leadership is about the risk aspect of it. What's the risk and liability to the organization? And so we, as at Shepard, we look at what are your operational securities and how does that affect your compliance, right?

52:41Because it's a defensible situation with regard to your compliance. There's always the battle of the enemy versus us and attacking the security. So there's always going to be an attack. What's the AI return on investment for taxpayers? And I ask that as all of us are the ones paying the bill, basically, for migration of data. It just comes down to that. Does it mean that we're going to get our passports faster? Does it mean, you know, what does it mean?

53:13Carol Massar:Frictionless, you know, when you're dealing with the government. Yeah, I do appreciate you putting me in that box. It's very nice of you. You know, what we see is incremental efficiencies. Tim White, Mike, Sierra, I was going to say. Exactly. No, what we're seeing is incremental efficiencies and speed. And what it's allowing us to do, for instance, is to move folks to other areas of the organization so that we can add better customer experience and faster to market and those types of things. So I see that being what we're allowing our customers, which are the ISVs, the cloud customers, going into the government, which then allows the government to be able to be faster with these new technology tools.

53:55How's that? That sounds good. I'm ready. Good, good.

53:57Carol Massar:That sounds like AI productivity to the government. All right. Yes. I'll take it. I'll take it. This is the Bloomberg Business Week Daily podcast. Available on Apple, Spotify, and anywhere else you get your podcasts. Listen live weekday afternoons from 2 to 5 p.m. Eastern on Bloomberg.com, the iHeartRadio app, TuneIn, and the Bloomberg Business app. You can also watch us live every weekday on YouTube and always on the Bloomberg Terminal.

54:33When you're running a business, the best days are the ones where priorities stay on track. For midsize and large companies, risk can affect multiple parts of the organization at once, from property and liability to cyber and regulatory challenges. At that level, managing risk becomes an ongoing discipline. At the Hartford, the focus is on helping businesses manage risk before it turns into something more disruptive. And when losses do happen, that work is paired with insurance coverage shaped by years of underwriting, risk engineering, and claims experience. Learn more at thehartford.com slash risk mitigation.

55:08Policies provided by Hartford Fire Insurance Company and its property and casualty affiliates, Hartford, Connecticut. Game night rush or any night of the week, really. Genius keeps every order moving. from online ordering to your kitchen to the front counter. Big League reliability for any business. That's genius. These days, it seems like AI agents are just about everywhere you turn, every field and every function. But without identity, you can't trust they'll serve your business instead of jeopardizing it. Fortunately, Okta helps you get identity right by securing your AI agent's identities, giving you a single layer of control, a single standard of trust.

55:48So whether an AI agent supports a single user or your entire enterprise, with Okta, you'll turn risk into opportunity. Secure every agent. Secure any agent. Okta secures AI.