 Welcome back to SuperCloud 4, where we're exploring the impact of AI and GenAI specifically and the transformative impacts it can have on industries. And we're super cloud excited to have Karen Dehut here with us today, who is the CEO of Google Public Sector. Karen, welcome to the program. It's great to see you and nice to meet you. Dave, it's great to be here on SuperCloud. Thank you for having me and what a great topic to talk about. Yeah, you bet. OK, so you're one year, almost exactly one year into your role as CEO of Google Public Sector. When you think back over the past 12 months, what are the major milestones that you feel are most notable for you and your team? Well, it's been an amazing year. First of all, I've learned a lot. Had the opportunity to speak with people across the world in terms of their desire for digital transformation and certainly how Google Public Sector and our incredible products can help. They tell me three things, Dave. They tell me three things that are important to them. First of all, that legacy IT is a huge issue. They have not been able to take advantage of the transformative effects of AI because they still have legacy IT in their platforms and in their organizations. And we can talk more about that. The second thing they talk about is they really need choice. They need flexibility. They need the opportunity to really leverage best of breed technologies. And they want to do that more rapidly than they do today. And then the last thing is they can't do it alone. They know that as public sector servants, whether they're serving citizens or the mission, they know that they need to use a broad collection of ecosystem partners. And Google is certainly super proud to be a part of that ecosystem and to really bring our Google magic to the mission of government. Yeah, thanks for that. I want to actually follow up on the whole legacy IT. And my sense is part of the challenge, of course, is you've got administrations change and edicts change. Sometimes you just can't flip the switch overnight. It takes sometimes years to, first of all, you got to figure out what to do, what's the right path. By the time you do that, then you got to implement. By the time you do that, everything changes. So it's hard for a lot of the practitioners within the public sector to stay on course. Is that just my perception or is that a real problem, that kind of revolving door? And can technology help, in many ways, technology probably helps create the problem. Can it help solve the problem? I think it is, of course, a challenge when you're constantly dealing with new leaders, new executives, new priorities. But I would step back from that for a moment and look back over the past 20 or 30 years and look at how technology platforms have shifted in that timeframe. So you start from mainframe, you move from mainframe to the personal computer, the personal computer to mobile, mobile to cloud. And now the most advanced technology shift, probably in our lifetime, is the shift to AI. The challenge with the public sector has been, they have not been able to keep pace, funding pace, as well as talent pace, with all of those technological shifts. So to really leverage the power of AI and generative AI, they have to move from mobile computing, from personal computing to cloud computing. And that's where digital transformation can really be accelerated. You know, it's interesting, you're right about the funding and people think, oh, wow, the government has so much money and taxes and everything else, but the government also has a lot of obligations, entitlements and things of that nature. Now, but this is a great setup because Google's always been an AI-first company. But up until the AI heard around the world just under a year ago, the broader market didn't seem that enthused. And it's amazing how the sentiment has changed, Karen. So now everybody's paying attention. In examples, Google has really stepped it up. Duet AI brings those kind of superpowers to your workspace offerings. Vertex AI, I'm super excited about because it allows a lot of more organizations to customize LLMs with their own data and bring sort of unique value there, barred, COTI. So lots of innovation going on at Google. But my question, Karen, is how are these advanced machine intelligent tools being used to transform public sector and the experience for citizens? It'd be great if you could comment on that and maybe give some examples. Sure. First of all, thank you for providing that listing of some of the things that we've done in AI and I hasten to add to your point, Google has been an AI-first company for a very, very long time. And so many of the products you use today have AI embedded. And you're right, as we were rolling out generative AI consumer products, it really captured the imagination of the globe and people started to ask questions and wanna understand more. But the reality is we've been serving up AI in our products and to our customers for a long time now. And I'll just give you a couple of examples. During the pandemic, states turned to Google to help them be able to deliver information to citizens about the pandemic, about vaccine safety in a fast, safe, accelerated way. And they turned to a generative AI tool called Contact Center AI, which creates, enables virtual agents to address questions of citizens in a much more effective and efficient way and allows really hard complicated cases to go to a human agent. So that's just an example of where AI is already in use and being used. Another example is states have turned to us to make sense of complicated documents and data that has to be captured in documents. We have doc AI as an example that allows people to have self-input into documents and for the input on those documents to be able to be leveraged into a large dataset and for AI to be applied. So these are simple ways that people can get started today that organizations can get started today with the power of AI and generative AI. But Dave, you mentioned vertex AI, large language models, generative AI. It's a super important topic. And I think government organizations and institutions are becoming more comfortable with that. What we're proud of with regard to vertex AI is it allows you to use generative tools on your private dataset and your data is not exposed to the public. And I think that's where some of the risk and concern around AI comes into play and we've created vertex AI specifically to address that concern. And I think, you know, that brings up a point, you know, in the early days of cloud, it was a situation where you would have like for instance, financial services organizations that I've talked to said, we'll never be in the cloud. And of course, you know, then the CIA adopted the cloud and then of course, defense agencies, we're doing some things that you can't talk about and still are I'm sure with data. And so the cloud is really the place where all this innovation occurs. You're hearing some similar things now in certain industries. And I wonder if it's the case in public sector where, oh, we're concerned about things like IP leakage and maybe we shouldn't do that in the cloud. Maybe we should do it on-prem. The problem with on-prem is they don't have the tooling and the innovation. Do you think, Karen, it's going to take, it's going to be a similar path where maybe initially there's some concerns but the cloud vendors generally Google specifically, and I want to talk about security in a moment, but your community, the technology community does such a good job of making people comfortable that the cloud is a safe place to do this work. Yeah, I mean, Google is the most secure cloud and I think that's for a couple of reasons. First of all, Google, the company was born in the cloud. We were never an on-prem operation. And so when you're born in the cloud, security is foundational to everything that you do. There are no seams in the way that when you move something from on-prem into the cloud, those same seams that exist on-prem exist in the cloud. We don't have that challenge because we were born in the cloud. I think that to your specific question around how do you get people comfortable with that, you have to show it to them. You have to prove to them, how is our platform more secure than what they have today? How do we ensure security throughout the life cycle of a mission, a life cycle of an application, et cetera? So I think it starts with showing them how that security is truly differentiated from what they have today. I mean, there is a lot of Gartner data out there that talks about incidences on cloud and how Google Cloud is the most secure. But sometimes you just have to show people the way it works. We are pioneers in zero trust, zero trust architecture, zero trust security and that notion of how to embed zero trust into an organization and an agency's applications into their cloud, their cloud security. Super important and we tell that story. The last thing I would add is a year ago we acquired Mandiant. Mandiant is the leading incident response and threat intelligence organization in the world serving commercial customers across the globe to make sure that their enterprises are secure. When you pair Mandiant Threat Intel and security services with Google Cloud and put those two things together we can tell a very pervasive story and show our customers how that security is end to end in our products. And I think, thank you for that. And I think the operative word that I heard there was embed because people talk about zero trust is a wonderful frameworks, but it's hard to operationalize them. The way you operationalize them is that they are fundamentally embedded into the platform. That's how end customers with all this that we're drowning in complexity can take advantage of these new architectures. And of course our audience is insanely focused on security. Super cloud three in August was all about AI and security and the sentiment from experts at the time was that the attackers, again at that time initially had the advantage thanks to gen AI tools for instance, helping attackers fish better. That's a simple example. But since then, we were covering Black Hat. My colleagues, you mentioned Mandy and we were at that event and that happened to be the same week that I was at CrowdStrike's Falcon which ironically is where I met Kevin Mandy for the first time. And the tech industry is moving very fast to level the playing field for defenders. And despite you still see high profile hacks like Caesars and MGM they're going to continue but what are you seeing as in terms specifically of the impact of gen AI in the public sector and how it's helping the good guys? Well, let me back up and talk a little bit about security in general. I think that what we would want people to really understand is that threat only continues to get more sophisticated and more complicated in the early part of 2023. We saw 35% increase in threats and cyber attacks. So it's only getting more pervasive. You mentioned Kevin who we are super happy to have as a part of Google Public Sector's board. He is on my board helping to advise us on exactly these matters that we're talking about today. We also talk a lot with Kevin about our proven zero trust architectures. And I think the reason I wanna start here is because this is where gen AI can really benefit from these proven architectures. Zero trust implies and ensures that you have only the individual with the right identity accessing the right machine authorizing the right code. I mean, when you think about that that is security baked in. And so when you start to think about how can generative AI really help in this case? Generative AI can really help you understand who your users are, what their identities are, what their accesses should be. You can apply generative AI to help you understand that and it can accelerate the implementation of zero trust and zero trust architectures. The thing I hear most commonly from customers around zero trust is it's really hard to implement and implement well. That is a true statement, but you can use generative AI tools to help accelerate that implementation and accelerate the knowledge of your organization and your users. So it's like trust but verify on the flip it. It's don't trust until you verify and that's really kind of what's here. And your point about the challenges of implementing again, I go back to embedding, if companies like Google can make this just part of the architecture then it becomes much simpler. It's there, it's fundamental. Let's talk a little bit more about Google and what it brings to the public sector. We know Google, it's got great tech. We talked about that. It emphasizes the value of its collaboration tools. When you go to things like Google Next as part of the Google Cloud, you've got the requisite compute and storage capabilities that any public cloud or hyperscale provider should have. But what's the unique value that Google delivers to the public sector? Clearly it's data platform. We talk a lot on theCUBE about BigQuery and we've talked about AI at the center. That's very impressive. But I'd love to hear your thoughts on this. Yeah, it's a great opportunity for me to talk about what we're doing specifically for our customers. So I thank you for that. Let me start out by saying that I think we have taken a very different approach to cloud for the public sector. What you see across the public sector are that most agencies are running less reliable, less feature rich, fortress versions of commercial cloud. And what we looked at and said, that doesn't really make sense. It doesn't scale and it doesn't scale economically. So we have taken a very different approach and said we are going to a credit for public sector organizations. Our commercial cloud. And we are upending this traditional incumbent way of thinking about cloud and saying you can access the full compute power of Google commercial cloud through our IL-5 implementation and accreditation of commercial cloud. So that's one thing that's super important. Of course, we already talked about the foundational concepts of zero trust and zero trust architectures. That's an area where we are fundamentally different and alone at the top of the stack when it comes to security and security features. I did also wanna talk about this idea of choice and offering choice to public sector customers. What they have resoundingly said is they need choice. Having a single cloud provider is just another version of vendor lock-in and they do not want that. And so what we have offered is a very robust and significant multi-cloud strategy where we have built Anthos, which is the world's first open cloud management platform which allows organizations to leverage all clouds and provides a management layer in a multi-cloud hybrid environment so that they can leverage the power of multiple clouds for whatever workloads they want. That eliminates vendor lock-in. It ensures open, as you know, Google is open by default, but ensures open because all clouds need to be able to work together. Software vendors need to be able to work across all cloud platforms. And so we believe that Anthos, along with our multi-cloud strategy is super differentiating. And of course the last area is where Google defaults to open. We have open architectures. We have open source software. I think we believe it greatly benefits the world because it encourages smart creatives to build, to build for the world and to build in a way that everybody can leverage the power of their software and their platforms. Cameron, I'm glad you brought up multi-cloud because it's a super cloud and of course the genesis of that was cross-cloud complexity. And so I'm interested, and by the way, I've talked to many customers that it's so complex, I just go monocloud and that's like, okay, but A, then you can't take advantage of best of breed. B, somebody else in your organization is doing some other cloud, I promise you. So this is a reality. And I think generally customers know that and admit that. So I'm curious how AI fits here. Does it, does it, because let's assume for a second you've got better AI than anybody. So a customer will say, I'm going to go to Google for my AI. Does it further, well, I guess it increases choice. That's goodness. Does it further the complexity or does it actually help solve multi-cloud complexity? Well, I mean, look, I think any enterprise, any agency is suffering from legacy IT and technical debt that they are trying to figure out how to address. We believe that cloud and multi-cloud allows them to move to these monolithic, vertically integrated operations or systems to a horizontal view of their data and their data enterprise. And so you don't need to rip and replace all of that legacy IT. You just need to make the data available in the cloud so that you can leverage AI and leverage multi-cloud, if you will. The reason I start there is because many organizations have started by saying, we're going to take this vertical monolith and we're going to put it in the cloud. So that's one instance of a cloud. And then another part of the organization takes another vertical monolith and they put it in a different instance of the cloud. So yes, it gets complicated, but once you have the data and the data enterprise in the cloud, you can really leverage AI tools to work across that horizontal. You can use the multi-cloud Anthos platform that I mentioned in order to understand how workloads are being used across those clouds and leveraging that insight to provide executive dashboards, et cetera. So of course it's complicated. Of course it requires great technical expertise, but more importantly, I believe it requires executive leaders to understand that in order to move from this environment of legacy IT and technical debt, the only way to move forward is by leveraging cloud and leveraging cloud and its capacities around their data enterprise and their AI and it's going to provide great benefit to them as an organization. I will close by making an observation and maybe you could comment. I would say in my years of working in technology markets, you know, there's no silver bullet. You've got to do the work and a new wave like AI, like you mentioned, some of the previous waves, gives executives an opportunity to really assess their portfolio of applications. And it starts with the value. Where is my organization getting value? And there's a lot of ways to understand that, but one is usage and how it supports the mission of the organization. And then at that point, you can really begin to figure out if you take that portfolio approach, where do I invest? Where do I stabilize? Where do I wind down or maybe manage decline? And what do I sunset? And in a tight budget environment, which is every IT organization, virtually every IT organization, that's a framework for making decisions. And then you can decide, okay, does it, should it be in the cloud? Is that where I want the innovation to go? Does it have to be on cloud? Maybe I can just over time wind it down on prem because it's not a critical area of investment. And that portfolio approach is ultimately going to give companies a framework or organizations a framework to make those types of decisions, but you got to do the work. Dave, I could not agree more. What I tell my customers is you just have to get started. I think we get into this analysis paralysis, fear of risk that we're taking on and it prevents an organization from moving forward. Pick a use case. Doesn't have to be a scary use case. Pick an area where you know that AI can be tremendously beneficial. Maybe it's a back office function, but something to get started, to show your organization that you need to move forward, that you need to leverage the power of these new emerging capabilities. And it's going to provide benefit to your organization, and to the citizenry or to the mission. And so we talk about getting started. We're super proud of the US Navy, for example, using workspace for seamless and secure connectivity and collaboration across some constituents in their environment. We're super proud of work that's being done at the Uniformed Services University Health Sciences, which is DoD's medical school where they're really using AI and clinical research. Again, these are not scary use cases. These are use cases that they just are showing. Look at the power of what this technology can do for us. And it's a starting point. Great advice value begets budget, I like to say. So thanks, Karen, for participating today in SuperCloud 4. We really appreciate your perspectives. Thank you, Dave. Thank you for having me on SuperCloud. Super appreciative of the time. Hey, you're very welcome. Thank you. All right, keep it right there for more SuperCloud 4 conversations live and on demand from theCUBE's Palo Alto Studios.